ai architect / engineer (agentic ai & llm architecture)

lead software engineer

platform engineer

senior data scientist

ai engineer

data scientist

ai data engineering lead vice president

BlackRock

<div><div><div><div>Locations: London, United Kingdom; Edinburgh, United Kingdom
Additional Locations: ED3 - 20 Brandon Street, Edinburgh</div></div></div></div>
 <div><h2 class="jobSectionHeader">Job description</h2>
<div>About this role
The VP AI Data Engineering Lead operates at the intersection of strategic influence, team leadership, and delivery excellence &mdash; playing a defining role in how AI-powered data and knowledge products are conceived, designed, and executed across the organization.
He/She/They lead a multi-team organization of AI agent engineers and data scientists &mdash; setting technical and delivery direction, building the team&rsquo;s capability, and holding accountability for the production systems powering the commercialized knowledge products.
He/She/They function as the most senior bridge between Product Management leadership, business functional stakeholders, and AI engineering &mdash; bringing the technical depth and strategic breadth to influence product vision while holding firm accountability for engineering delivery outcomes across multiple squads.
He/She/They sets the organizational standard for how product intent gets translated into technical reality, establishing engineering frameworks, authoring principles, and driving the culture of quality, accuracy, and ownership across the broader Product Lead community.
He/She/They are deeply experienced in the nuances of AI engineering, from agent workflow design and Vision AI evaluation to production validation, output-quality governance, and customer adoption of knowledge products. Beyond the delivery mandate, they are a builder of people and of technical leaders of tomorrow &mdash; developing high-performing teams and creating the conditions for others to do their best work.
This is a role for a leader who thinks in systems, acts with purpose, and measures their success not just by what ships, but by the commercial credibility and lasting organizational capability left behind.
Roles &amp; Responsibilities
<ul><li>Lead a team of AI agent engineers and data scientists &mdash; setting technical direction, managing delivery, driving performance, developing individual capability across the team, and building the talent bench across the function.
</li><li>Own end-to-end solution design &amp; delivery for complex AI features across multiple AI engineering squads building multi-agent, GenAI, and Vision AI workflows &mdash; ensuring consistency, quality, and strategic alignment at scale.
</li><li>Drive backlog prioritization at the product-area level, balancing customer value, technical feasibility, AI accuracy expectations, model/vision constraints, and team capacity
</li><li>Run sprint planning, team stand-ups, and retrospectives; create the operating rhythm and working environment for engineers and data scientists to do their best work
</li><li>Proactively engage and act as the bridge between the Product Management, business stakeholders and AI engineering &mdash; influencing product vision &amp; feature prioritization (definition, scope, and sequencing) from deep understanding of technical possibility and commercial reality influence feature.
</li><li>Partner with Product Managers to shape feature roadmaps, bringing technical and AI-specific insight that meaningfully influences what gets built, when, and at what quality bar.
</li><li>Drive structured refinement sessions with the team, ensuring stories are technically complete and aligned on solution approach before development begins.
</li><li>Define and enforce quality standards for user story delivery &mdash; including extraction accuracy, edge-case coverage, agent behaviour expectations, and non-functional requirements
</li><li>Lead post-implementation validation efforts &mdash; coordinating UAT, output-quality reviews, production monitoring, and closing the loop with stakeholders on commercial outcomes
</li><li>Support product activation and customer adoption &mdash; translating delivery milestones into customer-facing readiness for data/knowledge product rollout
</li><li>Define and champion organization-wide standards for user story authoring, solution design, backlog management, and delivery quality for AI-powered knowledge products
</li><li>Lead complex, cross-functional AI initiatives from discovery through delivery &mdash; managing dependencies, risks, and stakeholder expectations across teams.
</li><li>Coach and mentor team members, conduct performance conversations, and contribute to hiring decisions for the AI engineering and data science team.
</li><li>Establish frameworks for post-implementation validation, output-quality governance, production monitoring, and customer success during product activation and adoption at scale
</li><li>Identify systemic delivery bottlenecks and drive process improvements that raise velocity and quality across the product organization
</li><li>Build and mentor a high-performing team of AI agent engineers, and data scientists &mdash; driving hiring, onboarding, performance management, and career development at scale
</li><li>Shape organizational design, team structure, and operating model for the AI data engineering function as the business scales
</li></ul>Required Skills &amp; Experience
Technical Skills
<ul><li>Minimum 6-8 years of experience in AI Engineering Delivery Lead, or AI Program Lead, or Engineering Manager roles, with at-least 2-3 years operating as AI Engineering Principal within a SaaS, AI, or data-product organization.
</li><li>Deep expertise and Proven experience in AI solution design and technical scoping for AI-driven features &mdash; ideally including GenAI, LLM-based capabilities, Vision AI, and multi-agent workflows.
</li><li>Strong command of scaled Agile delivery, cross-team dependency management, and delivery governance frameworks, backlog management, sprint planning, and Agile delivery tooling at scale (Jira, Confluence, Miro, or equivalent)
</li><li>Ability to engage meaningfully with AI engineers and data scientists on architecture decisions, agent orchestration, prompt design, Vision AI trade-offs, and model behaviour
</li><li>Fluency in the AI product development lifecycle &mdash; extraction accuracy, model evaluation, prompt engineering considerations, non-deterministic behaviour, and production monitoring
</li><li>Solid understanding of evaluation approaches for AI outputs &mdash; accuracy metrics, ground-truth validation, human-in-the-loop review, and output-quality benchmarking
</li><li>Familiarity with unstructured data extraction challenges across document, image, and multimodal inputs.
</li><li>Advanced grasp of product analytics, AI output-quality measurement, and outcome-based evaluation frameworks for data/knowledge products
</li><li>Deep understanding of responsible AI principles (accuracy governance, data provenance, and user trust as they relate to commercialized AI outputs) and their practical implications for feature design, accuracy governance, customer trust, and regulatory considerations
</li></ul>Non-Technical &amp; Interpersonal Skills
<ul><li>Executive-level communication skills &mdash; able to operate fluidly between engineering stand-ups and boardroom strategy conversations.
</li><li>Excellent communication and stakeholder management skills &mdash; able to drive alignment across product, commercial, engineering, and domain-expert audiences
</li><li>Strong strategic thinking &mdash; able to connect present engineering decisions &amp; strategy to long-term commercial positioning of AI knowledge/data products.
</li><li>Strong analytical and structured problem-solving approach &mdash; breaks down complex extraction and knowledge-structuring problems into clear, actionable paths forward
</li><li>Emotional intelligence and people-first leadership style &mdash; able to inspire, coach, and hold a diverse team of engineers and scientists to a high bar; earns trust quickly across diverse stakeholder groups including customers, commercial, and technical teams.
</li><li>Business acumen &mdash; understands the fundamentals of financials services industry and/or software/data product business, and how product output quality &amp; timeliness directly affects customer trust and revenue.
</li></ul>Leadership &amp; Ownership
<ul><li>Proven track record of building, leading, and developing teams of engineers, data scientists, or technical specialists in an AI or data product context at scale.
</li><li>Demonstrable experience influencing product vision and feature strategy at the leadership level &mdash; shaping what gets built, not just how.
</li><li>Experience establishing organization-wide standards, frameworks, and practices that persist beyond individual initiatives.
</li><li>Proven ability to set technical direction, manage delivery, and drive accountability across a cross-functional team.
</li><li>Track record of mentoring individuals, running performance conversations, and contributing to hiring and team-building.
</li><li>Courage to push back on feature scope or timelines when extraction accuracy, reliability, or commercial viability &mdash; or team sustainability &mdash; are at risk
</li><li>Proven track record of owning complex AI delivery outcomes end-to-end, including post-launch validation and adoption.
</li><li>Hands-on experience with hiring, team design, performance management, and succession planning for technical AI teams.
</li><li>Ability to hold the bar on quality and delivery while advocating for the team &mdash; protecting focus, escalating constraints, and making hard prioritization calls
</li><li>A builder-of-builders mindset &mdash; measures success by the capability and culture left behind, not just the features shipped.
</li></ul>What This Role Offers
<ul><li>Direct leadership of a high performing team of AI agent engineers and data scientists working on commercially impactful AI systems &amp; knowledge product portfolio &mdash; with meaningful autonomy and ownership.
</li><li>Direct influence over organizational direction &mdash; working closely with executive leadership on product vision, hiring, and operating model decisions.
</li><li>A meaningful seat at the table in shaping product &amp; engineering strategy, feature prioritization, and delivery practices for commercialized AI capabilities
</li><li>A platform to build and lead a world-class organization of AI engineers, data scientists, and Product Leads &mdash; creating lasting capability in commercialized AI.
</li><li>Direct exposure to emerging AI capabilities &mdash; multi-agent orchestration, GenAI, Vision AI &mdash; applied to real commercial problems at scale.
</li></ul><ul><li>A clear path toward head-of-Engineering function leadership roles, with investment in mentorship, external learning, and executive development.
</li></ul>Our benefits
To help you stay energized, engaged and inspired, we offer a wide range of employee benefits including: retirement investment and tools designed to help you in building a sound financial future; access to education reimbursement; comprehensive resources to support your physical health and emotional well-being; family support programs; and Flexible Time Off (FTO) so you can relax, recharge and be there for the people you care about.
Our hybrid work model
BlackRock&rsquo;s hybrid work model is designed to enable a culture of collaboration and apprenticeship that enriches the experience of our employees, while supporting flexibility for all. Employees are currently required to work at least 4 days in the office per week, with the flexibility to work from home 1 day a week. Some business groups may require more time in the office due to their roles and responsibilities. We remain focused on increasing the impactful moments that arise when we work together in person &ndash; aligned with our commitment to performance and innovation. As a new joiner, you can count on this hybrid model to accelerate your learning and onboarding experience here at BlackRock. 
 
Guidance on AI use for candidates 
 
At BlackRock, AI has long been part of how we work &ndash; enhancing decision-making, improving operations, and helping us deliver better outcomes for clients. We encourage candidates to use AI thoughtfully to learn, prepare, and work more effectively; but during our interview process, we want to focus on getting to know you through your own experiences, thinking, and judgment. To support you, we&rsquo;ve provided guidance( opens in new window) on when and how to use AI during our hiring process so you can approach each step with confidence and showcase your best self. 
 
 
About BlackRock 
 
At BlackRock, we are all connected by one mission: to help more and more people experience financial well-being. Our clients, and the people they serve, are saving for retirement, paying for their children&rsquo;s educations, buying homes and starting businesses. Their investments also help to strengthen the global economy: support businesses small and large; finance infrastructure projects that connect and power cities; and facilitate innovations that drive progress. 
 
This mission would not be possible without our smartest investment &ndash; the one we make in our employees. It&rsquo;s why we&rsquo;re dedicated to creating an environment where our colleagues feel welcomed, valued and supported with networks, benefits and development opportunities to help them thrive. 
 
To learn more about BlackRock, please visit Careers.BlackRock.com( opens in new window). We also encourage you to get to know us on LinkedIn( opens in new window), Instagram( opens in new window), YouTube( opens in new window), X( opens in new window), and TikTok( opens in new window). 
 
BlackRock is proud to be an Equal Opportunity Employer. We evaluate qualified applicants without regard to age, disability, race, religion, sex, sexual orientation and other protected characteristics at law.
</div><div>Job Requisition #
 
R264955</div></div>

AI Data Engineering Lead, Vice President

<div>
 
 Job Description
 
 
 
 We&rsquo;re seeking a future team member for the role of
 
 AI-Forward Software Engineer &mdash; AI Transformation Office
 
 ,
 
 Senior Vice President
 
 to join our team. This role is located in
 
 London
 
 .
 
 
 We are looking for a hands-on, AI-forward engineer to build and ship production-grade GenAI and agentic automation solutions as part of BNY's centralized AI Transformation Office. This is not a traditional engineering role - we are not looking for engineers who use AI tools occasionally. We need engineers who have fundamentally changed how they work: using tools like Claude Code and Windsurf daily, moving faster because of it, and bringing that AI-first mindset to everything from architecture decisions to code reviews.
 
 
 In this role, you&rsquo;ll make an impact in the following ways:
 
 
 <ul>
 <li>
 Analytical skills - understand the business problem first; leverage AI tools to accelerate solution design, not replace the thinking
 </li>
 <li>
 Initiative &amp; Ownership - run with tasks end-to-end, from scoping and prototyping to deployment, using AI-native tooling throughout - not just for coding, but across the entire workflow including design, testing, and documentation
 </li>
 <li>
 Build and contribute to AI-forward architecture standards - including prompt engineering patterns, agentic workflow design, and LLM integration guidelines
 </li>
 <li>
 Work with Product Owners, LOB stakeholders, and architects to design, prototype, and deliver AI-powered solutions spanning automation, workflow orchestration, and client-facing tooling
 </li>
 <li>
 Participate in code reviews with an AI-first lens - evaluating not just the code, but how effectively AI tooling was leveraged in the build
 </li>
 <li>
 Software engineering experience with demonstrable, recent use of AI-native development tools as a core part of daily workflow - not a side habit
 
 
 </li>
 </ul>
 To be successful in this role, we&rsquo;re seeking the following:
 
 
 <ul>
 <li>
 Required Skills
 </li>
 <ul>
 <li>
 Daily proficiency with AI coding tools such as Claude Code, Windsurf, Cursor, or GitHub Copilot - this is a baseline requirement, not a differentiator
 </li>
 <li>
 Python and/or Java for backend service development
 </li>
 <li>
 LLM integration experience - OpenAI, Anthropic, or equivalent APIs
 </li>
 <li>
 MCP, REST APIs, Microservices Architecture
 </li>
 <li>
 Cloud platforms - AWS, Azure, or GCP
 </li>
 </ul>
 <li>
 Preferred
 </li>
 <ul>
 <li>
 Agentic framework experience - LangChain, LangGraph, AutoGen, or similar
 </li>
 <li>
 RAG pipeline design and vector database experience (Pinecone, Weaviate, pgvector)
 </li>
 <li>
 Agile / SDLC tooling - Jira, Git, CI/CD pipelines
 
 </li>
 </ul>
 </ul>
 
 About Us
 
 
 
 At BNY, our culture allows us to run our company better and enables employees&rsquo; growth and success. As a leading global financial services company at the heart of the global financial system, we influence nearly 20% of the world&rsquo;s investible assets. Every day, our teams harness cutting-edge AI and breakthrough technologies to collaborate with clients, driving transformative solutions that redefine industries and uplift communities worldwide.
 
 
 Recognized as a top destination for innovators, BNY is where bold ideas meet advanced technology and exceptional talent. Together, we power the future of finance &ndash; and this is what is all about. Join us and be part of something extraordinary.
 
 
 
 About The Team
 
 
 
 At BNY, our culture speaks for itself, check out the latest BNY news at: BNY Newsroom &amp; BNY LinkedIn
 
 
 
 Here&rsquo;s a Few Of Our Recent Awards
 
 
 
 <ul>
 <li>
 America&rsquo;s Most Innovative Companies, Fortune, 2025
 </li>
 <li>
 World&rsquo;s Most Admired Companies, Fortune 2025
 </li>
 <li>
 &ldquo;Most Just Companies&rdquo;, Just Capital and CNBC, 2025
 
 
 </li>
 </ul>
 
 Our Benefits And Rewards
 
 
 
 BNY offers highly competitive compensation, benefits, and wellbeing programs rooted in a strong culture of excellence and our pay-for-performance philosophy. We provide access to flexible global resources and tools for your life&rsquo;s journey. Focus on your health, foster your personal resilience, and reach your financial goals as a valued member of our team, along with generous paid leaves, including paid volunteer time, that can support you and your family through moments that matter.
 
 
 BNY is an Equal Employment Opportunity/Affirmative Action Employer - Underrepresented racial and ethnic groups/Females/Individuals with Disabilities/Protected Veterans.
</div>

AI-Forward Software Engineer — AI Transformation Office, Senior Vice President

JPMorganChase

<div>JOB DESCRIPTION 
 
 
Join a firmwide team accelerating our data, analytics, and AI journey through highly governed, high-impact initiatives. In this role, you will help define how data is made available to power new products and AI models at scale. You will partner across lines of business and corporate functions to design architecture, toolchains, user-centric processes, and control frameworks that improve how data is developed and deployed&mdash;safely, efficiently, and at scale.
As a Vice President for Strategy Lead for Data Development Lifecycle (DDLC) in the Firmwide Chief Data Office, you will lead the development and execution of new architecture, tool chains, user-centric design, and control frameworks that transform the firm's data development process from concept to delivery. You will partner with firmwide teams, lines of business, and corporate functions, oversee crucial aspects of the lifecycle, and engage leaders across the business. A background in data science or a related technical field and excellent written and oral communication skills are valued given the visibility of this role.
Job responsibilities:
<ul><li>Define the process for data development from the perspective of data practitioners across all lifecycle stages with clear roles and responsibilities</li>
<li>Partner with technology leaders to develop a firmwide reference architecture supporting data development and testing in controlled environments</li>
<li>Partner with risk management and controls to develop a control framework for managing data risks</li>
<li>Manage end-to-end delivery of changes to key platforms and toolchains supporting DDLC&mdash;from proof of concept through deployment</li>
<li>Collaborate and align with architects, data engineers, and technologists to achieve business outcomes</li>
<li>Identify opportunities for continuous development and improvement of the DDLC, ensuring changes are done safely and at scale</li>
<li>Demonstrate self-motivation and tenacity, working with a high degree of independence</li>
<li>Develop executive-level presentation decks, documents, and white papers to communicate complex concepts and recommendations</li>
<li>Communicate effectively across diverse stakeholders in decision-making and strategy implementation</li>
<li>Work in a highly collaborative, matrixed environment to build consensus</li>
<li>Assist in identifying, escalating, and mitigating project risks that could impair execution of the strategy</li>
</ul>Required qualifications, capabilities, and skills:
<ul><li>7+ years' experience in financial services, data/technology, or related consulting</li>
<li>Deep data science experience with consulting for end-to-end delivery and exceptional analytical, problem-solving, communication, and presentation skills</li>
<li>Ability to develop executive-level decks, documents, and white papers to communicate complex concepts and recommendations</li>
<li>Ability to work in a highly collaborative, matrixed environment to build consensus and excellent stakeholder management and coordination skills</li>
<li>Structured thinker and effective communicator with excellent written communication skills and ability to crisply articulate complex technical concepts to senior audiences</li>
<li>Deep domain expertise (knowledge of clients, products, services) coupled with deep expertise in the data (applications systems, BI and AI applications) used to manage and execute strategy across multiple business units</li>
<li>Strong knowledge of data mesh architecture and data product concepts</li>
</ul>Preferred qualifications, capabilities, and skills:
<ul><li>Experience in roadmap creation and execution, aligning and leading business operations to strategic organizational goals</li>
<li>Strong understanding of AI/ML technologies and their application in data management/governance</li>
<li>Understanding of control and risk management concepts</li>
<li>Strong product management and project management skills</li>
</ul>ABOUT US
 
 
J.P. Morgan is a global leader in financial services, providing strategic advice and products to the world's most prominent corporations, governments, wealthy individuals and institutional investors. Our first-class business in a first-class way approach to serving clients drives everything we do. We strive to build trusted, long-term partnerships to help our clients achieve their business objectives. 
<div><div>We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation. 
</div></div> 
 
ABOUT THE TEAM
 
 
Our professionals in our Corporate Functions cover a diverse range of areas from finance and risk to human resources and marketing. Our corporate teams are an essential part of our company, ensuring that we're setting our businesses, clients, customers and employees up for success.</div>

Vice President - Strategy Lead for Data Development Lifecycle (DDLC)

Bank of China

<div>Financial Management department is in charge of planning, organising, directing and controlling the financial activities of the Bank. The department performs a variety of financial functions, including accounting and financial reporting, fixed asset and expenses management, budget and management reporting, taxation (indirect and direct), regulatory reporting, treasury (asset and liability management) and capital management. As an Assistant Vice President - Axiom Developer, you will support regulatory reporting change, primarily across Capital and Liquidity reporting, with an emphasis on UK PRA requirements. The role contributes to both regulatory delivery and the strategic Regulatory Datamart. You will play a critical role focusing on the Basel 3.1 implementation, ensuring the Bank&rsquo;s reporting framework is robust, scalable, and compliant with the latest Prudential Regulation Authority (PRA) requirements in Axiom. This is a full time 12 months fixed term contract position.
Key responsibilities<ul><li>
Support Basel 3.1 implementation including Credit Risk, Market Risk, and Operational Risk and Liquidity Risk</li><li>
Work extensively with Axiom data dictionary mapping, data lineage, and solution upgrade activities to ensure accurate regulatory reporting</li><li>
Oversee, build, and maintain a centralised regulatory DataMart, ensuring seamless data lineage from source systems to Axiom</li><li>
Translate regulatory requirements and business specifications into scalable technical solutions within Axiom platform</li><li>
Analyse regulatory guidance and provide Subject Matter Expert (SME) input to ensure end-to-end compliance and regulatory standards</li><li>
Act as the primary technical liaison between the Regulatory Policy, BAU, and IT delivery teams</li><li>
Drive the automation of regulatory returns including COREP, FINREP, Liquidity, and PRA regulatory returns, reducing manual intervention and improve efficiency</li><li>
Document reporting processes, controls, and key project delivery decisions</li></ul>
Requirements<ul><li>
Degree educated in Finance, Accounting or other relevant subject</li><li>
Solid experience as an Axiom Developer</li><li>
Experience with large-scale Data Warehouse/DataMart projects integrated with Axiom</li><li>
Prior experience in a Bank or Financial Institution supporting major regulatory transition</li><li>
Good understanding of regulatory rule sets (Basel 3.1), reporting instructions, and controls</li><li>
Excellent communication skills with a comfort level in dealing with clients</li><li>
Highly organised and able to work in a fast paced environment</li><li>
Attention to detail</li></ul>
Having a presence in the UK for more than 90 years, Bank of China London Branch has been providing an excellent financial service to the market and maintain its competitive edge as an international bank operated in the UK. It has employees in over 33 countries, and it is one of the most internationalised overseas branch in the Bank of China Group. The Bank values the diversity of its employees and aims to create an inclusive environment where everyone can speak up and enjoy the equal opportunities to grow both personally and professionally.</div>

Assistant Vice President - Axiom Developer

International Rescue Committee

<div>The International Rescue Committee (IRC) responds to the world's worst humanitarian crises, helping to restore health, safety, education, economic wellbeing, and power to people devastated by conflict and disaster. Founded in 1933 at the call of Albert Einstein, the IRC is one of the world's largest international humanitarian non-governmental organizations (INGO), at work in more than 40 countries and 29 U.S. cities helping people to survive, reclaim control of their future and strengthen their communities. A force for humanity, IRC employees deliver lasting impact by restoring safety, dignity and hope to millions. If you're a solutions-driven, passionate change-maker, come join us in positively impacting the lives of millions of people world-wide for a better future.
Job Role Overview
The Director, AI Security is a newly created senior leadership role responsible for building, leading, and continuously maturing the IRC&rsquo;s AI security function. As AI agents and AI-powered tools proliferate across the business, this role sets the organizational direction for securing AI systems &mdash; from initial design through production deployment, ongoing governance, and team development.
This is a high-visibility, cross-functional leadership role that sits at the intersection of security engineering, risk management, and emerging technology. The Director, AI Security will advise the CISO, build and develop a dedicated AI security team, own the function&rsquo;s budget, and partner with Security Operations, Identity &amp; Access Management, Governance Risk &amp; Compliance, and business unit technology teams to ensure AI adoption is secure by design.
Key Responsibilities
AI Security Strategy &amp; Governance<ul><li>
Define, own, and continuously mature the IRC's AI security strategy and program roadmap</li><li>
Establish and maintain the organization-wide AI agent registry &mdash; a governed inventory of all AI agents in production, including their purpose, permissions, data access, and accountable owners</li><li>
Develop and publish secure-by-default standards, frameworks, and reference architectures for internal AI agent development</li><li>
Create and enforce AI security policies covering agent development, deployment, monitoring, and decommissioning</li><li>
Report AI security risk posture, program progress, and emerging threats to the CISO and senior leadership on a regular cadence; serve as a key member of the security leadership team</li></ul>
Security Risk Assessment &amp; Review<ul><li>
Coordinate and perform GIS security reviews within the organization's AI governance framework, ensuring AI platforms, agents, and use cases receive appropriate security assessment and approval prior to production deployment.</li><li>
Partner with AI Governance, Privacy, Legal, and Technology stakeholders to support the AI intake, assessment, and stage-gating process, providing security expertise, control requirements, and risk-based recommendations throughout the solution lifecycle.</li><li>
Perform security risk assessments and classify AI platforms, agents, and use cases according to the approved risk-tiering model, applying review, control, and approval requirements proportionate to risk.</li><li>
Conduct a structured controls assessment for every use case, validating that mandatory security baseline requirements are met &mdash; including least-privilege access, credential management, audit logging, data minimization, human-in-the-loop checkpoints, and kill switch capability</li><li>
Issue formal, documented approval decisions for every reviewed use case &mdash; Approved, Approved with Conditions, or Not Approved &mdash; with a full written rationale recorded in the AI agent registry to maintain an auditable approval history</li><li>
Manage defined SLA timelines for all reviews (Tier 1: 5 business days, Tier 2: 10 business days, Tier 3: 15 business days) to ensure security review does not become a blocker to business unit velocity</li><li>
Conduct periodic reassessments of all active agents on a risk-appropriate cycle &mdash; annually for Tier 1, semi-annually for Tier 2, and quarterly for Tier 3 &mdash; and trigger immediate out-of-cycle reviews whenever a material change is made to an agent's capabilities, data access, or toolset</li><li>
Monitor the evolving AI threat landscape on an ongoing basis and proactively assess whether newly discovered attack techniques &mdash; including new prompt injection methods, jailbreaks, or model-specific vulnerabilities &mdash; expose any currently approved use cases, initiating remediation where required</li><li>
Lead post-incident reassessments for any active agent involved in a security incident, updating the agent's approval status and controls requirements based on findings</li><li>
Evaluate third-party AI tools, models, and platforms for security risk prior to organizational adoption</li><li>
Maintain a risk register specific to AI systems, tracking identified vulnerabilities, mitigations, and residual risk</li><li>
Report aggregate review metrics to the CISO on a regular cadence &mdash; including number of use cases reviewed, approval rates by tier, common findings, and AI risk distribution across business units &mdash; providing organizational visibility into the AI risk posture</li></ul>
Technical Oversight &amp; Controls<ul><li>
Define technical security requirements for AI agents including least-privilege access, prompt injection defenses, output filtering, audit logging, and human-in-the-loop controls</li><li>
Build, lead, and develop a team of AI security engineers responsible for implementing and validating controls across the AI agent development lifecycle</li><li>
Own and resource red team and adversarial testing programs targeting AI systems, ensuring adequate coverage through the AI Red Team Engineer and contracted specialists</li><li>
Drive adoption of secure coding practices and security tooling within AI development workflows</li></ul>
Identity &amp; Data Security Coordination<ul><li>
Establish governance frameworks with the IAM team to ensure AI agent identities, service accounts, and credentials are provisioned and governed under least-privilege principles across the organization</li><li>
Set data security standards with the ML/Data Security Analyst to ensure sensitive data &mdash; including PII, PHI, and proprietary information &mdash; is handled correctly throughout AI agent workflows, and hold teams accountable to those standards</li><li>
Define data classification requirements for information flowing through AI systems, including what data may and may not be included in model context</li></ul>
Incident Response<ul><li>
Develop and maintain AI-specific incident response runbooks covering scenarios such as prompt injection attacks, rogue agent behavior, credential compromise, and data leakage via AI systems</li><li>
Serve as executive sponsor and escalation point for significant AI-related security incidents, ensuring the organization maintains a tested, capable incident response function</li><li>
Conduct post-incident reviews and drive lessons learned back into the AI security program</li></ul>
Regulatory &amp; Compliance Alignment<ul><li>
Serve as the organization's primary subject matter expert on AI-specific regulatory requirements including the EU AI Act, NIST AI Risk Management Framework (AI RMF), GDPR as applied to AI systems, and emerging regional AI legislation</li><li>
Partner with the GRC team to map AI security controls to compliance obligations and maintain evidence for audits</li><li>
Monitor the evolving AI regulatory landscape and proactively advise leadership on upcoming obligations</li></ul>
People Leadership &amp; Team Development<ul><li>
Recruit, hire, onboard, and develop a high-performing AI security team, including AI security engineers, a red team engineer, and a data/ML security analyst</li><li>
Set clear team goals, conduct regular performance reviews, and create development plans that grow individual skills and advance careers</li><li>
Foster a team culture of continuous learning, given the rapidly evolving AI threat landscape, and ensure team members maintain current expertise in AI security techniques and tooling</li></ul>
Vendor Management<ul><li>
Lead vendor evaluation and selection for AI security tooling, negotiating contracts and managing ongoing relationships with key security vendors and managed service providers</li><li>
Develop a multi-year AI security roadmap aligned to IRC risk appetite, and evolving regulatory obligations</li></ul>
Working Relationships
Internal:<ul><li>
CISO, ITLT, Security Operations &amp; Engineering lead and team, Identity &amp; Access Management (IAM) lead and team, Governance, Risk &amp; Compliance (GRC) lead, AI Review Panel lead and team, Office of General Council team, AI &amp; Program tech engineering and team, Data Architecture lead and engineering Team</li></ul>
External:<ul><li>
AI and Security Vendors &mdash; ongoing for product evaluation, contracts, and threat intel</li><li>
Industry Peers &amp; Research Communities &mdash; active participation in ISACs, working groups, and conferences</li></ul>
Required Qualifications
Education<ul><li>
Bachelor's degree in Computer Science, Information Security, Cybersecurity, or a related technical field</li><li>
Advanced degree (Master's or equivalent) preferred but not required where experience is demonstrably strong</li></ul>
Experience<ul><li>
10+ years of experience in information security, with at least 4-5 years in a people management or senior security leadership role</li><li>
Demonstrated hands-on experience securing AI/ML systems, LLM-based applications, or agentic AI workflows</li><li>
Proven experience conducting threat modeling, security architecture reviews, and risk assessments for complex, distributed systems</li><li>
Experience building and leading security teams, including hiring, developing, and retaining talent in a fast-moving technical domain</li><li>
Track record of working cross-functionally with engineering, product, legal, and compliance teams; experience owning and managing a security budget including tooling, vendor, and headcount decisions</li><li>
Prior experience with incident response and managing security incidents involving automated or AI-driven systems is strongly preferred</li><li>
Demonstrated experience managing and developing a team of security professionals, including hiring, performance management, and career development</li></ul>
This is a remote position open to internal candidates based in countries where IRC operates who have the right to work in their location. Successful candidates will be hired on a local employment contract and according to local salary scale.
Compensation: (US Pay Range: $158,492-$184,536/yr; UK Pay Range: &pound;77,499-&pound;93,814/yr) Posted pay ranges apply to US-based candidates. Ranges are based on various factors including the labor market, job type, internal equity, and budget. Exact offers are calibrated by work location, individual candidate experience and skills relative to the defined job requirements. 
PROFESSIONAL STANDARDS
All International Rescue Committee workers must adhere to the core values and principles outlined in IRC Way - Standards for Professional Conduct. Our Standards are Integrity, Service, Equality and Accountability. In accordance with these values, the IRC operates and enforces policies on Safeguarding, Conflicts of Interest, Fiscal Integrity, and Reporting Wrongdoing and Protection from Retaliation. IRC is committed to take all necessary preventive measures and create an environment where people feel safe, and to take all necessary actions and corrective measures when harm occurs. IRC builds teams of professionals who promote critical reflection, power sharing, debate, and objectivity to deliver the best possible services to our clients.
Cookies: https://careers.rescue.org/us/en/cookiesettings
Compensation: Posted pay ranges apply to US-based candidates. Ranges are based on various factors including the labor market, job type, internal equity, and budget. Exact offers are calibrated by work location, individual candidate experience and skills relative to the defined job requirements.
US Benefits: We offer a comprehensive and highly competitive set of benefits. In the US, these include: 10 sick days, 10 US holidays, 20-25 paid time off days depending on role and tenure, medical insurance starting at $163 per month, dental starting at $6.50 per month, and vision starting at $5 per month, FSA for healthcare and commuter costs, a 403b retirement savings plans with immediately vested matching, disability &amp; life insurance, and an Employee Assistance Program which is available to our staff and their families to support counseling and care in times of crisis and mental health struggles.
Equal Opportunity Employer: IRC is an Equal Opportunity Employer. IRC considers all applicants on the basis of merit without regard to race, sex, color, national origin, religion, sexual orientation, age, marital status, veteran status, disability or any other characteristic protected by applicable law.
#li-1</div>

Director, AI Security

Talan

<div>Company Description 
Talan Data x AI is a leading Data Management and Analytics consultancy, working closely with leading software vendors and top industry experts across a range of sectors, unlocking value and insight from their data. At Talan Data x AI, innovation is at the heart of our client offerings, and we help companies to further improve their efficiency with modern processes and technologies, such as Machine Learning (ML) and Artificial Intelligence (AI). 
Job Description 
As our AI practice scales, we are seeking an experienced AI Architect / Engineer to act as the senior technical authority shaping how we design and deliver next-generation AI solutions. This is a role for someone who has moved beyond building individual models to architecting entire systems: agentic platforms, LLM-powered applications, and the production infrastructure that makes them dependable at enterprise scale.
You will sit at the intersection of strategy and delivery, operating across multiple client engagements simultaneously. In the early phases you will shape solutions, validate technical approaches, and translate ambiguous business problems into robust, deployable architectures. As engagements mature, you will provide the technical oversight that keeps delivery teams aligned to the original design intent. Your influence will be felt in pre-sales conversations, solution blueprints, and the technical standards that define how our practice builds.
This is a hands on architectural role, not a purely advisory one. We expect you to remain close to the code, to prototype where it accelerates a decision, and to set a credible technical example for the engineers and data scientists you guide.
Required skills &amp; experience:<ul><li>
Lead end-to-end solution architecture for AI and LLM-based systems, spanning data, integration, infrastructure, and deployment.</li><li>
Design agentic architectures and multi-agent orchestration patterns, defining how LLMs, tools, APIs, and retrieval layers interact reliably.</li><li>
Shape early-stage engagements (scoping, solutioning, estimation, and pre-sales) turning client ambition into deliverable technical plans.</li><li>
Provide technical validation and quality oversight across several concurrent projects, mitigating risk before it reaches delivery.</li><li>
Define LLM integration and prompting strategies, including RAG, fine-tuning, evaluation, and guardrailing approaches.</li><li>
Establish MLOps and LLMOps practices that ensure solutions are observable, testable, and production ready.</li><li>
Set architectural standards, reusable patterns, and reference implementations that raise the quality bar across the practice.</li><li>
Partner with Responsible AI colleagues to embed safety, security, and governance into solution designs from the outset.</li></ul> 

Qualifications 
To qualify for this role, you must have:
<ul><li>Minimum 5 years in AI architecture or AI engineering, ideally 10+, with a track record of production deployments.</li><li>
Deep expertise in LLMs, agent frameworks (e.g. LangGraph, AutoGen, Semantic Kernel), API design, and orchestration.</li><li>
Strong cloud engineering experience.</li><li>
Proven MLOps / LLMOps capability &mdash; CI/CD for models, monitoring, evaluation, and cost optimisation.</li><li>
Hands-on software engineering background (Python and modern tooling) underpinning your architectural decisions.</li><li>
Comfort managing multiple engagements at once, with pragmatic judgement on trade-offs and delivery risk.</li></ul>
Ideally, you&rsquo;ll also have, but not essential:<ul><li>
Experience in consulting, professional services, or pre-sales environments.</li><li>
Exposure to enterprise-scale, regulated AI deployments (financial services, public sector, healthcare).</li><li>
Familiarity with vector databases, knowledge graphs, and advanced retrieval techniques.</li><li>
Relevant cloud or AI certifications.</li></ul>
You must be:<ul><li>
Willing to work on client sites, potentially for extended periods.</li><li>
Willing to travel for work purposes and be happy to stay away from home for extended periods.</li><li>
Eligible to work in the UK without restriction.</li></ul> 
#TalanUK #LI-HB1 
Additional Information 
Compensation &amp; Benefits Package:<ul><li>
BDP Plus &ndash; A reward programme whereby you accrue points to trade against a 3-month paid sabbatical or cash equivalent.</li><li>
25 days holiday + bank holidays.</li><li>
5 days holiday buy/sell option.</li><li>
Private medical insurance.</li><li>
Life cover.</li><li>
Cycle to work scheme.</li><li>
Eligibility for company pension scheme (5% employer contribution, salary sacrifice option).</li><li>
Employee assistance programme.</li><li>
Bespoke online learning via Udemy for Business.</li></ul>
Why join:
You will be a founding technical voice in a practice that is investing decisively in AI. The work is varied, intellectually demanding, and commercially significant, you will shape solutions that reach production, not slideware. You will have the autonomy to define how we build, the support of a collaborative multidisciplinary team, and a clear platform to grow into a practice-leading technical figure.</div>

AI Architect / Engineer (Agentic AI & LLM Architecture)

Cognism

<div><div><h2 class="jobSectionHeader">WHO ARE WE</h2>

Cognism is the leading provider of European B2B data and sales intelligence. Ambitious businesses of every size use our platform to discover, connect, and engage with qualified decision-makers faster and close more deals. Headquartered in London with global offices, Cognism's contact data and contextual signals are trusted by thousands of revenue teams to eliminate the guesswork from prospecting.</div>
The Role

At Cognism, the security of our data, our systems and our clients' systems is a business priority. Information security is embedded in the way we work, and we are driving a culture where the fastest path is the securest path. As the function continues to mature, we are now hiring for a Director of Security Engineering &amp; Operations to report directly to our CISO. In this role you will own and drive the technical security strategy for Cognism's web and data products, as well as our corporate environment. You will be responsible for designing a security programme that protects our most sensitive assets: our data, our data fusion engine and the logic that powers it. As a trusted partner to our R&amp;D leadership team you will help to define and drive the long-term security engineering maturity roadmap, driving alignment across engineering leaders, product leadership and IT. If you're energised by the idea of shaping measurable security processes and controls, from the ground up, aligning engineering around secure-by-design principles, and elevating operational excellence, then this is the role for you. This is a rare opportunity to define the technical security vision for a dataintensive product at a moment where AI, scale, and engineering velocity are creating new and exciting challenges. You will shape how Cognism builds securely for the next decade. 


What success looks like

Within 12 months, you will have:
<ul>
<li>Delivered a unified security engineering roadmap aligned with engineering leadership.</li>
<li>Matured secure SDLC adoption across Web and Data engineering.</li>
<li>Improved MTTD/MTTR through stronger SOC operations.</li>
<li>Invested in and mentored a team with clear ownership, KPIs, and engineering trust.</li>
<li>Reduced engineering friction by creating pragmatic, developerfriendly guardrails</li></ul> 


What You'll Own

Security Strategy &amp; Engineering Integration
<ul>
<li>Define and own Cognism's technical security strategy that seeks to embed security-by-design within our web and data products, our data fusion engine and pipelines, and our corporate landscape. You will drive a strategy that is pragmatic, risk-ranked, and aligned to engineering velocity.</li>
<li>Work directly with product and technology leadership as a strategic partner. You will drive ownership and accountability, clearly agreeing ways of working between your team and product and technology teams.</li>
<li>Set and direct a secure SDLC strategy that engineers engage with, coaching and mentoring our application security engineer with running our threat modelling program, embedding security in CI/CD, and iteratively improving our vulnerability management processes.</li>
<li>Partner with engineering leadership to ensure risk-driven supply chain management across our product, ensuring what we bring in doesn't undermine what we protect.</li>
<li>Work directly with our Director of IT operations to ensure our corporate security posture is mitigating risk and empowering our employees to be as secure as possible, through guardrails that protect unacceptable risk but don't stifle innovation.</li></ul> 


Data &amp; AI Security
<ul>
<li>Partner with our VP of Data Engineering to strengthen the security of our enrichment engine, data pipelines, and warehouse ecosystems.</li>
<li>Direct a strategy that considers security across the full data stack - from ingestion through to the warehouse - with a focus on access governance, data classification, and secrets management as non-negotiables.</li>
<li>Define how Cognism embeds AI securely as LLMs and agentic workflows move deeper into the product and our technology teams' operations.</li>
<li>Partner with our CISO to shape and implement an AI security posture that is embedded in strong security foundations, helping us stay ahead of the threat landscape rather than reacting to it.</li></ul> 


Detection, Response &amp; SOC Partnership
<ul>
<li>Own the strategic relationship with our 24/7 outsourced SOC holding them to a high standard on threat hunting, threat intelligence utilisation, and automated response, not just SLA compliance.</li>
<li>Ensure Cognism has a holistic, well-maintained SIEM that reflects how we operate and improves continuously as the threat landscape evolves.</li>
<li>Build the internal team into a trusted escalation layer, with clear incident response playbooks, rehearsed escalation paths, and a feedback loop that sharpens detection over time.</li></ul> 


Team &amp; Culture 

<ul>
<li>Lead a team of application and infrastructure security engineers, setting the standard for technical excellence and deep partnership with their engineering counterparts.</li>
<li>Build a security culture where developers raise security questions early, understand threat models, and own remediations, not because policy requires it, but because the culture makes it natural.</li>
<li>Be the security leader Cognism's engineers want in the room: credible enough to be trusted, collaborative enough to be included, and strategic enough to make it count.</li></ul> 


What We Need

Leadership &amp; influence
<ul>
<li>Demonstrated experience building security programmes from scratch or transforming them significantly in a product-led, engineering-first company.</li>
<li>A track record of influencing engineering culture and earning trust, not enforcing it.</li>
<li>Experience managing external security partners, (e.g 24/7 Security Operations Centre, penetration testing 3rd parties) and raising their performance through clear accountability, not just contract reviews.</li>
<li>Able to communicate risk in business terms to exec and board audiences, and technical terms to engineers, without losing precision in either direction.</li></ul> 


Technical foundation
<ul>
<li>Strong AppSec expertise (OWASP, API security, SAST/DAST, SDLC) with practical threat modelling experience &ndash; enough to challenge and coach our most senior application security engineers.</li>
<li>Handson understanding of data security, cloud data warehouses, and pipeline integrity &ndash; enough to ensure we are driving the right programme of work across our technology department.</li>
<li>Cloud security fluency with working knowledge of container and Kubernetes security, IAM design, and cloud-native security tooling &ndash; enough to clearly identify, prioritise and challenge solutions for implementing security in our cloud environment.</li>
<li>Working knowledge of AI/LLM security risks: enough depth to assess integrations, define guardrails, and evolve the programme as the technology does.</li></ul> 


Mindset
<ul>
<li>Risk-based by instinct: prioritises based on both technical and business impact</li>
<li>Builder mentality: energised by creating structure where there isn't any, pragmatic about sequencing, and focused on outcomes over coverage.</li>
<li>Genuinely curious about AI, not just its security risks, but its potential to improve how security is done.</li>
</ul><div>
<h2 class="jobSectionHeader">WHY COGNISM</h2>

At Cognism, we're not just building a company - we're building an inclusive community of brilliant, diverse people who support, challenge, and inspire each other every day. If you're looking for a place where your work truly makes an impact, you're in the right spot!

Our values aren't just words on a page&mdash;they guide how we work, how we treat each other, and how we grow together. They shape our culture, drive our success, and ensure that everyone feels valued, heard, and empowered to do their best work.

Here's what we stand for:

 We Own the Outcome Together. 
 We Deeply Understand our Customers. 
 We Celebrate Impact Wherever It Comes From.

At Cognism, we are committed to fostering an inclusive, diverse, and supportive workplace. We welcome applications from individuals typically underrepresented in tech, so if this role excites you but you're unsure if you meet every requirement, we encourage you to apply!</div></div>

Director, Security Engineering & Operations

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