ai researcher

Novo Nordisk, Inc.

<div><div><div><div><div><p>Associate Director, AI Products Engineering, London
</p></div></div></div></div><div><div><div><div><b>Category: </b>Data &amp; AI
</div></div></div></div><div><div><div><div><b>Location:
</b>London, London, GB<br>
</div></div></div></div><div></div><div><div><div><div><div><div><div>Are you passionate about machine learning, AI, and data sciences? The Data &amp; AI Engineering function is a global organisation within R&amp;D Business Unit at Novo Nordisk, shaping the data foundations and intelligent infrastructure, and next-generation agentic solutions across the organization. Together we can create life-changing innovations for patients.</div></div><div><br>
<div>
</div></div><div><div><b>The Position</b></div>
</div>
<div><div>As Associate Director, you will provide strategic engineering leadership for the development of scalable and robust AI products, including agentic applications for content authoring, knowledge management, and compliance automation. You will lead a portfolio spanning early research, pre-clinical, and clinical development, ensuring agentic AI initiatives progress from proof-of-value to production. The role is accountable for establishing the data foundations and agentic AI infrastructure that support Novo Nordisk's R&amp;D AI ambitions, while driving business impact through the orchestration of complex cross-functional initiatives and stakeholder collaborations in a quality- and governance-focused environment.</div></div><div><br>
<div>
</div></div><div><div><b>Furthermore, you will be responsible for:</b></div>
</div>
<div><ul><li><div>Defining and driving the AI product infrastructure strategy for R&amp;D, enabling an integrated ecosystem of Agentic AI solutions</div>
</li>
</ul></div><div><ul><li><div>Ensure robust and scalable delivery of AI capabilities (data foundations, infrastructure, MLOps), with a strong focus on quality, traceability, risk management, and governance readiness. Transforming scientific and operational data into trusted, scalable AI solutions that accelerate innovation, improve efficiency, and support better business outcomes across R&amp;D.</div>
</li>
</ul></div><div><ul><li><div>Developing and executing short- and long-term strategies for AI engineering and AI data foundations, aligning R&amp;D and Enterprise AI priorities through internal partnerships and external collaborations.</div>
</li>
</ul></div><div><ul><li><div>Driving cross-functional initiatives and influence senior stakeholders to remove complexity, accelerate AI adoption, and enable sustainable AI-driven transformation across the organization.</div>
</li>
</ul></div><div><ul><li><div>Leading the delivery of technology innovation across a complex stakeholder landscape and scientific environment, balancing evolving business priorities while identifying the highest-impact opportunities for AI deployment.</div></li></ul><br>
</div>
<div></div><div><div><b>Qualifications</b></div>
</div>
<div><div><b>To thrive and succeed, we expect you to have:</b></div>
</div>
<div><ul><li><div>Degree in Computer Science, Bioinformatics, Information Technology, Engineering, or a related field.</div>
</li>
</ul></div><div><ul><li><div>Strong background in Artificial Intelligence, Machine Learning, Data Science, or Product Development with a strong focus on product engineering. Solid understanding of AI engineering, data foundations, cloud technologies, and scalable AI solution development.</div>
</li>
</ul></div><div><ul><li><div>Proven experience leading teams or working in a strategic consulting capacity, with a track record of delivering complex AI and Machine Learning initiatives across data engineering, AI/ML research, and IT platforms.</div>
</li>
</ul></div><div><ul><li><div>Experience engaging with senior business stakeholders and translating business needs into technology and AI strategies. Strong stakeholder management, communication, and influencing skills across complex organizational environments.</div>
</li>
</ul></div></div><div><div><ul><li><div>Ability to represent the organization in collaboration with external technology partners and AI providers within areas such as Agentic AI, AI engineering, and data platforms.</div>
</li>
</ul></div><div><ul><li><div>A curious, collaborative, and visible leadership style, with a passion for innovation and continuous learning.</div></li></ul><br>
</div>
<div></div><div><div><b>About the Department</b></div>
</div>
<div><div>You will join a recently established AI Product Engineering team focused on enabling the next generation of AI solutions across R&amp;D. Working closely with Data Science and AI stakeholders across multiple global locations, the team is developing advanced Agentic AI capabilities in areas such as Gen AI-driven content authoring, research assistance agents, knowledge management agents, and compliance automation through AI.</div>
</div>
<div><div>The team plays a key role in shaping scalable AI platforms, engineering standards, and technology foundations that support the sustainable development of AI solutions across a complex and evolving data landscape.</div></div><div><br>
<div>
</div></div><div><div><b>Working at Novo Nordisk</b></div>
</div>
<div><div>At Novo Nordisk, we don't wait for change. We drive it. We're a dynamic company in an even more dynamic industry, and we know that what got us to where we are today is not necessarily what will make us successful in the future. We embrace the spirit of experimentation, striving for excellence without fixating perfection. We never shy away from opportunities to develop, we seize them. From research and development, through manufacturing, marketing, and sales &ndash; we're all working to move the needle on patient care.</div></div><div><br>
<div>
</div></div><div><div><b>What we offer</b></div>
<div>
At Novo Nordisk, you&rsquo;ll join a global healthcare company with a unique culture and strong results. We offer continuous learning, career development, and benefits tailored to your life and career stage.</div>
<div><b>
Salary:</b><b> </b>For this role, the Annual Base Salary ranges from 87,680.00 to 137,660.00 GBP, corresponding to the level of the position.</div>
<div>
The placement within the salary range will be assessed during the recruitment process based on the candidate&rsquo;s skills, competencies, knowledge, and relevant experience.</div>
<div><b>
Incentives and Benefits: </b>The salary package may include short-term and/or long-term incentives as well as other employee benefits based on position level, location, functional area and relevant market benchmarks.</div>
<div>
Learn more about our Reward Philosophy here.</div></div><div><br>
<div>
</div></div></div><div><div><b>Deadline</b></div>
</div>
<div><div><b>17th July 2026</b></div>
</div><div>
We commit to an inclusive recruitment process and equality of opportunity for all our job applicants.</div><br>
<div></div>
<div>
At Novo Nordisk, we're not chasing quick fixes &ndash; we're creating lasting change for long-term health. For over 100 years, we've been driven by a single purpose: to defeat serious chronic diseases and help millions of people live healthier lives. This dedication fuels our constant curiosity and inspires us to push the boundaries of what's possible in healthcare. We embrace diverse perspectives, seek out bold ideas, and build partnerships rooted in shared purpose. Together, we're making healthcare more accessible, treating and preventing diseases, and pioneering solutions that create change spanning generations. When you join us, you become part of something bigger &ndash; a legacy of impact that reaches far beyond today.</div></div></div></div></div></div>

Associate Director, AI Products Engineering, London

JPMorganChase

<div><b>JOB DESCRIPTION</b><br>
<br>
<br>
<p>Client360 is one of JPMorgan Chase Commercial &amp; Investment Bank's strategic pillars, building the future of our business, and unifying the data fabric of all client activity. Combined with external data, Client360 leverages this unique data asset to deliver insight and enterprise rewiring at scale.</p>
<p>Are you passionate about Agentic AI and operational transformation? As the Agentic AI Operations Lead, you will drive the development and management of agentic AI solutions, enabling intelligent automation across Client360. You will help shape the future of Client360, enhance client engagement, and accelerate business-wide growth and transformation.</p>
<p>Within Data, Digital and AI, as the C360 Agentic AI Operations Lead you will be responsible for the product development and technology build of the Agentic AI workbench and integrated control environment. On establishing this platform, you will work hand-in-hand with the platform and data operations teams to pivot their day-to-day activities into agent led workflows.</p>
<p></p><p><b>Job Responsibilities</b></p>
<ul><li>Partners with architecture and engineering to establish the future state architecture of the Agentic AI workbench, leveraging market leading agent orchestration, evaluation and connectivity protocols to keep C360 on the cutting edge of agent-led operations.</li>
<li>Manages the delivery, optimization, and integration of agentic AI operations for Client360, ensuring alignment with CIB-wide goals and organizational objectives.</li>
<li>Participates in the planning, execution, and risk management of AI operations programs, including frameworks for AI deployment, monitoring, and operational efficiency.</li>
<li>Supports agentic AI initiatives, from ideation and development to implementation and continuous improvement, adapting to evolving business needs and managing risks.</li>
<li>Coaches and mentors junior team members on best practices in AI operations management, business analysis, stakeholder engagement, and change management, enabling effective delivery of objectives.</li>
<li>Collaborates with engineering, operations, and business teams to maintain and enhance agentic AI platforms, ensuring scalability, reliability, and user-centricity.</li>
<li>Helps define the user experience for Client360 agentic AI operations, focusing on process optimization, data-driven insights, and stakeholder satisfaction.</li>
<li>Supports foundational business processes that enable Client360 through AI-driven solutions.</li>
<li>Assists in establishing and monitoring key performance indicators, ensuring agentic AI operations deliver measurable business value and support long-term strategic goals.</li>
<li>Leverages analytics and AI tools to help derive actionable insights from integrated data and third-party sources, supporting comprehensive client profiles and improved decision-making.</li>
<li>Understands the needs of internal teams and anticipates future requirements, collaborating with stakeholders across Markets, Payments, Global Banking, and the Private Bank to drive consistency and adoption of agentic AI solutions.</li>
<li>Utilizes agentic AI operations to deliver personalized client experiences, streamline operations, and enhance decision-making, while supporting regulatory compliance and risk management.</li>
</ul><p></p><p><b>Required qualifications, capabilities, and skills</b>
</p><ul><li>5+ years of experience or equivalent expertise delivering AI operations, business initiatives, or transformation programs.</li>
<li>Strong knowledge of agentic AI systems, service delivery, business process improvement, strategic planning, and data analytics.</li>
<li>Demonstrated ability to support adoption of key AI operations lifecycle activities including discovery, ideation, development, requirements definition, and value management.</li>
<li>Experience supporting change within organizations and managing stakeholders across multiple functions.</li>
<li>Track record of contributing to large-scale AI integration and analytics projects.</li>
<li>Good understanding of AI integration techniques, data governance, regulatory compliance, and operational risk management.</li>
<li>Customer-centric mindset with the ability to prioritize and deliver what clients and stakeholders need.</li>
<li>Experience in working with cross-functional teams and managing stakeholders to drive AI innovation.</li>
<li>Excellent problem-solving skills and strategic thinking about agentic AI operations and their impact on organizational objectives.</li>
<li>Strong communication and interpersonal skills, with the ability to articulate and present complex AI concepts and insights to both technical and non-technical audiences.</li>
<li>Experience with emerging technologies and best practices in AI operations, business analytics, and CRM.</li>
</ul><p></p><p><b>Preferred qualifications, capabilities, and skills
</b></p><ul><li>Experience working in a highly matrixed, complex organization.</li>
<li>Experience in AI operations management, business process management, CRM systems, or related fields within a financial institution.</li>
<li>Bachelor's degree in Business, Data Science, Computer Science, or a related field; advanced degree preferred.</li>
<li>Experience in ensuring customers and stakeholders are engaged and positive about the AI solutions delivered.</li><br>
</ul><div></div><br>
<b>ABOUT US</b>
<br>
<br>
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.<br>
<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.<br>
</div></div><br>
<br>
<b>ABOUT THE TEAM</b>
<br>
<br>
J.P. Morgan's Commercial &amp; Investment Bank is a global leader across banking, markets, securities services and payments. Corporations, governments and institutions throughout the world entrust us with their business in more than 100 countries. The Commercial &amp; Investment Bank provides strategic advice, raises capital, manages risk and extends liquidity in markets around the world.</div>

Agentic AI Ops Lead

International Swaps and Derivatives Association

<div><div><p>June 30, 2026</p>
<p><b>Job Title:</b> Assistant Director, Artificial Intelligence</p>
<p><b>Reports to:</b> Senior Director, Digital Transformation, Analytics</p>
<p><b>Location:</b> London</p>
</div><div><p><b>Job purpose</b><br>
This is a hands-on role. The successful candidate will architect and build production AI systems directly, while owning delivery, quality, evaluation, and partner management across the AI Solutions Lab portfolio. The role reports to the Senior Director of Digital Transformation and head of the AI Solutions Lab.</p><br>
<p></p>
<p><b>
Duties and responsibilities</b></p>
<ul>
<li>Deliver the next phase of the ISDA AI Solutions Lab&rsquo;s buildout, helping move current AI initiatives from prototype/MVP stage toward robust, scalable and member-ready delivery. Architect and build the next phase of AI agents, external and internal.</li>
<li>Own the design and delivery of AI solutions that make ISDA standards and digital solutions more accessible, usable and AI-ready for members.</li>
<li>Help shape and scale the ISDA Knowledge Base and Assistant as the governed foundation for AI-enabled access to ISDA standards, taxonomies and related IP.</li>
<li>Oversee enhancement of priority AI capabilities including the CDM Coder, DRR Translator, Tracer, cross-jurisdiction analysis and AI legal opinions initiatives.</li>
<li>Help drive development and rollout of internal AI capabilities and agents aligned with the internal AI deployment roadmap.</li>
<li>Define product requirements, broader Agents orchestration, architecture direction, evaluation harnesses and quality standards and delivery priorities across the AI Solutions Lab portfolio.</li>
<li>Work closely with internal SMEs across CDM, DRR, legal, IT and product teams to ensure solutions are accurate, grounded and useful in real workflows.</li>
<li>Reach out to members for pulse checks and convert member and stakeholder feedback into roadmap decisions, product refinements and delivery choices to maximize adoption.</li>
<li>Help define practical connectivity and delivery models, including MCP servers and packaged AI Skills, so members can consume ISDA AI capabilities safely within their own environments.</li>
<li>Contribute to broader ISDA AI strategy development, including alignment between external member-facing AI solutions and internal AI deployment priorities.</li>
<li>Lead AI quality, guardrails and governance across the Lab&rsquo;s solutions, including evaluation harnesses, groundedness and traceability checks, observability and tracing, confidence frameworks, security and safe use boundaries, both internally and externally.</li>
<li>Own cost aware design of AI workloads, balancing performance and reliability against inference and infrastructure spend.</li>
<li>Manage relevant external partners and specialist vendors, ensuring work is aligned to ISDA&rsquo;s priorities, timelines, architecture and ownership model.</li>
<li>Support the Senior Director including for executive and board reporting by articulating progress, key risks, delivery needs and strategic value in a clear and concise way.</li>
<li>Help build a durable internal AI capability for ISDA that protects ISDA IP, accelerates adoption of ISDA standards and reinforces ISDA&rsquo;s strategic position in the market<b><i>.</i></b></li></ul><br>
<p></p>
<p><b>
Relevant Skills / Abilities</b></p>
<ul>
<li>Strong senior-level experience (at least five years) leading the design and delivery of AI-enabled products or platforms from prototype through controlled rollout and production, with a demonstrable track record of shipping production AI systems that serve real users.</li>
<li>Hands-on engineering ability in Python (and ideally TypeScript/React for front end UI) and Java, and comfortable building production systems directly.</li>
<li>Deep understanding of LLMs, retrieval-augmented generation (including hybrid retrieval across semantic, graph and keyword search, with reranking and embedding-model selection), knowledge bases, knowledge graphs and ontologies, agentic workflows and skills, evaluation methods (eval harnesses, LLM-as-judge, groundedness and faithfulness metrics, tracing), and model risk controls.</li>
<li>Experience building secure, scalable and reliable AI solutions in enterprise environments, including governance, permissions, auditability and data protection including private retrieval architectures and ensuring proprietary data is not exposed to external model providers</li>
<li>Hands-on AWS experience (Bedrock, Neptune, OpenSearch, Lambda) is very important. Strong engineers able to ramp quickly will also be considered. Cost-aware design of inference and infrastructure spend is expected.</li>
<li>Proven ability to translate complex domain knowledge into usable AI products, ideally in financial markets, regulatory technology, legal tech, standards or data-intensive environments; or a demonstrated ability to ramp quickly on a complex domain.</li>
<li>Strong product and solution architecture skills, with the ability to define use cases, prioritize roadmap items and align technical delivery with strategic business outcomes.</li>
<li>Experience overseeing external vendors, technology partners and proof-of-concept work, while retaining internal control of direction, quality and IP.</li>
<li>Ability to work closely with subject matter experts to refine AI tools iteratively and turn specialist feedback into practical product improvements.</li>
<li>Strong grasp of structured data, taxonomies, ontology-style data models and mappings across complex standards or schemas.</li>
<li>Experience with user testing, controlled pilots, adoption planning, training and feedback loops for specialist user populations.</li>
<li>Strong judgment on AI risks, including hallucination, groundedness, security, explainability, confidence scoring and safe deployment boundaries.</li>
<li>Degree in Computer Science, Artificial Intelligence, Data Science, Software Engineering, or a related discipline, or equivalent practical experience, is desirable.</li>
<li>Excellent communication skills, including the ability to understand member issues, to work across the organization and influence and align stakeholders, and to brief senior management and explain technical issues in concise business language.</li>
<li>Demonstrated ability to operate in a lean, hands-on environment, balancing strategy, execution and stakeholder engagement.</li></ul></div></div><p></p>

Assistant Director, Artificial Intelligence, London

Accenture

<div><p><b>YOU ARE</b></p><p>
As a hands-on Infrastructure architect, you are an early-career engineer who learns and grows while contributing hands-on to the AI and machine learning infrastructure that powers real-world applications. Under the guidance of senior architects and engineers, you'll develop practical skills in coding, testing, configuring, deploying, monitoring, and troubleshooting AI systems and the infrastructure they run on. Day to day, you'll write and test code and deployment scripts, help configure cloud and on-premises compute resources such as GPU clusters and distributed training environments, deploy AI systems and models into production, and support data pipelines that feed AI and ML workflows. You'll learn to monitor AI systems and infrastructure health across both InfraOps and MLOps disciplines, perform AI monitoring to track model and system performance, and troubleshoot issues across the computational stack with mentorship and support. This is a hands-on, learning-focused where you build expertise across modern tools and platforms &mdash; including container orchestration, model serving, CI/CD pipelines, InfraOps, MLOps, and AI monitoring &mdash; while making meaningful contributions to infrastructure that enables AI-driven busin</p><p>
ess outcomes.</p><p></p><p><b>
THE WORK</b></p><ul><li>
Write, test, and debug code and scripts for AI infrastructure tasks, including automation and tooling, under the guidance of senior engineers.</li><li>
Develop and maintain infrastructure and software deployment scripts to support reliable, repeatable releases of AI systems and models.</li><li>
Configure and provision compute resources across cloud and on-premises environments, including GPU clusters and distributed training setups.</li><li>
Deploy AI systems and machine learning models into production infrastructure, following established processes and best practices.</li><li>
Deploy data pipelines that feed AI and ML workflows, ensuring data is available, clean, and reliable.</li><li>
Assist with container orchestration and model serving, learning tools such as Docker, Kubernetes, and model deployment frameworks.</li><li>
Support and maintain CI/CD pipelines for automating the build, test, and deployment of AI infrastructure and applications.</li><li>
Monitor AI systems and infrastructure health across InfraOps and MLOps disciplines, tracking performance, reliability, and resource utilization.</li><li>
Perform AI monitoring to track model performance, detect drift or degradation, and surface issues for review.</li><li>
Troubleshoot and help resolve issues across the computational stack &mdash; hardware, networking, software, and models &mdash; with mentorship and support.</li><li>
Document configurations, processes, and procedures to maintain clear, repeatable, and shareable knowledge across the team.</li><li>
Collaborate with senior architects and engineers, participating in code reviews, team discussions, and knowledge-sharing sessions to grow technical skills.</li><li>
Apply security, cost-efficiency, and scalability best practices as you learn them, contributing to well-managed and responsible infrastructure.</li></ul></div>
<br>
<div><p><b>EDUCATION</b></p><ul><li>
Bachelor's Degree in Computer Science, Computer Engineering, related Engineering field</li></ul><p></p><p><b>
BASIC (REQUIRED) QUALIFICATION</b></p><ul><li>
Work or coursework experience with AI/ML or Computer engineering or Computer science.</li><li>
Coding, building, monitoring, troubleshooting applications of AI/ML models; selecting, designing and infrastructure for deploying and running them on premise or on public cloud.</li><li>
Strong understanding of AI and machine learning as a subject.</li><li>
Strong understanding of computing infrastructure a subject, preferred knowledge of AI infrastructure.</li><li>
Proficiency in programming languages such as Python, Java, or C++.</li></ul></div><p></p>

AI Infrastructure Architecture Analyst

<div><b>Role description</b><p><b><br>
Technical Product Owner / Technical Product Manager &ndash; Agentic AI</b></p>
<p><b>
Location:</b> Leeds (Hybrid)<br>
<b>Engagement Type:</b> Contract (Inside IR35) or Fixed-Term Employment<br>
<b>Start Date:</b> ASAP</p><br>
<p></p>
<p>
We are seeking an experienced Technical Product Owner / Technical Product Manager to support a strategic Device Management Modernisation initiative leveraging Agentic AI capabilities.</p>
<p>
Working closely with Product, Engineering, Architecture, and Business stakeholders, you will drive product outcomes, translate business needs into technical solutions, and help deliver innovative AI-powered capabilities while ensuring continuity of existing business processes.</p><br>
<p></p>
<p><b>
Key Responsibilities:</b></p>
<ul>
<li>Own and drive product outcomes across the modernisation programme.</li>
<li>Define product priorities, roadmap, and requirements in collaboration with business and technology stakeholders.</li>
<li>Translate business objectives into clear user stories and delivery-ready requirements.</li>
<li>Manage and prioritise the product backlog to maximise business value.</li>
<li>Partner with Engineering and Architecture teams to deliver scalable, high-quality solutions.</li>
<li>Support the design and delivery of Agentic AI use cases and workflows.</li>
<li>Embed Responsible AI, governance, security, and compliance considerations into product delivery.</li>
<li>Act as the primary bridge between Product, Engineering, and Business teams, ensuring alignment throughout delivery.</li></ul><br>
<p></p>
<p><b>
What You'll Bring:</b></p>
<p><b>
Product &amp; Delivery</b></p>
<ul>
<li>Proven experience as a Technical Product Manager, Technical Product Owner, or similar role in a technology-led environment.</li>
<li>Strong understanding of product operating models, product lifecycle management, and Agile delivery.</li>
<li>Experience leading technology transformation or modernisation initiatives.</li>
<li>Ability to translate business requirements into engineering-ready solutions.</li></ul><br>
<p></p>
<p><b>
Agentic AI &amp; GenAI</b></p>
<p><b>
Working knowledge of:</b></p>
<ul>
<li>Agentic AI concepts, including multi-agent orchestration, RAG, AI tool/API integration, memory frameworks, and Responsible AI controls.</li>
<li>Large Language Models (LLMs), prompt engineering, evaluation approaches, and cost, latency, and accuracy trade-offs.</li></ul><br>
<p></p>
<p><b>
Technical &amp; Stakeholder Skills</b></p>
<ul>
<li>Experience working closely with Engineering, Architecture, and Product teams.</li>
<li>Understanding of cloud-native and API-driven architectures.</li>
<li>Strong stakeholder management, communication, and influencing skills.</li>
<li>Ability to engage effectively with both technical and non-technical audiences.</li></ul><br>
<p></p>
<p><b>
Nice to Have</b></p>
<ul>
<li>Experience delivering AI, GenAI, Machine Learning, or Intelligent Automation solutions.</li>
<li>Experience with Microsoft AI, Azure AI, OpenAI, Copilot, or similar AI platforms.</li>
<li>Background in enterprise technology transformation or device management environments.</li></ul><br>
<p></p>
<p><b>
Why Join Us?</b></p>
<p>
Join a high-profile transformation programme and play a key role in shaping the next generation of AI-enabled products while working alongside leading product, engineering, and AI specialists.</p>
<p></p>
<p><b>Hurry &amp; Apply!</b><br>
<b>#UST</b></p><p></p><b><br>
Skills</b><p><br>
agentic ai,life cycle management,artificial intelligence,product management,</p><b><br>
About UST</b><br>
UST is a global digital transformation solutions provider. For more than 20 years, UST has worked side by side with the world&rsquo;s best companies to make a real impact through transformation. Powered by technology, inspired by people and led by purpose, UST partners with their clients from design to operation. With deep domain expertise and a future-proof philosophy, UST embeds innovation and agility into their clients&rsquo; organizations. With over 30,000 employees in 30 countries, UST builds for boundless impact&mdash;touching billions of lives in the process.</div>

Technical Product Owner / Technical Product Manager – Agentic AI (Lead I - Software Engineering)

Talan

<div><b>Company Description</b><p><br>
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).</p><b><br>
Job Description</b><p><br>
As AI moves from experimentation to enterprise-wide adoption, doing it responsibly has become a commercial necessity, not just an ethical one. We are looking for a Responsible AI Specialist to ensure the solutions we design and the advice we give to clients are trustworthy, compliant, and fair by design. This is a role for someone who can translate principles (fairness, transparency, accountability) into practical frameworks that engineering teams and clients can actually apply.</p><p>
You will be a connective figure across the practice: advising delivery teams on ethical and regulatory risk, contributing to client governance conversations, and helping shape the standards by which we build. You do not need to be a deep technical engineer, but you must understand how AI systems work, where they fail, and what good governance looks like in practice, particularly as regulation such as the EU AI Act reshapes expectations.</p><p>
This is a growing area of strategic importance, offering significant scope to define our approach and to become a recognised voice in responsible AI.</p><p><b>
Required skills &amp; experience:</b></p><ul><li>
Define and implement Responsible AI frameworks, policies, and practical guidelines across the practice.</li><li>
Advise project teams on ethical AI design, risk identification, and mitigation throughout the delivery lifecycle.</li><li>
Conduct AI risk and impact assessments, and embed fairness, transparency, and accountability into solutions.</li><li>
Contribute to client conversations on AI governance, risk, and regulatory readiness.</li><li>
Monitor evolving regulation (EU AI Act, ICO guidance, emerging standards) and translate it into actionable guidance.</li><li>
Support internal capability building, raising awareness and competence in responsible AI across teams.</li><li>
Partner with architects and data scientists to operationalise governance &mdash; model documentation, evaluation, and guardrails.</li></ul><br>
<b>
Qualifications</b><p><b><br>
To qualify for this role, you must have:
</b></p><ul><li>Minimum 3 years in AI ethics, governance, policy, risk, compliance, or a closely related regulatory field.</li><li>
Sound understanding of AI concepts, risks, and failure modes (deep technical implementation not required).</li><li>
Working knowledge of relevant regulation and standards, including the EU AI Act.</li><li>
Strong stakeholder communication skills, able to engage both technical teams and senior business audiences.</li><li>
Ability to turn principles into pragmatic, usable frameworks and processes.</li></ul><p><b>
Ideally, you&rsquo;ll also have, but not essential:</b></p><ul><li>
Experience in consulting or advisory roles.</li><li>
Familiarity with assurance frameworks (ISO/IEC 42001, NIST AI RMF).</li><li>
Background in data protection, privacy, or model risk management.</li><li>
Exposure to fairness, bias, and explainability tooling.</li></ul><p><b>
You must be:</b></p><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><p>
#TalanUK #LI-HB1</p><b><br>
Additional Information</b><p><b><br>
Compensation &amp; Benefits Package:</b></p><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><p><b>
Why join:</b></p><p>
Responsible AI is central to how we earn client trust and differentiate our practice. You will have the rare chance to shape this capability from an influential position, combining ethics, regulation, and real delivery in work that genuinely matters. As adoption and scrutiny grow, so will your impact and your profile.</p></div>

Responsible AI Specialist (Governance, Ethics & Compliance)

<div><p><b>YOU ARE</b></p><p></p><p>
As a hands-on Infrastructure Architect, you are an experienced engineer with several years in infrastructure engineering who now takes on more complex, higher-impact work designing and optimizing the AI and machine learning infrastructure that powers real-world applications. Working alongside senior architects and engineers &mdash; and increasingly leading your own workstreams &mdash; you apply proven skills in coding, testing, configuring, deploying, monitoring, and troubleshooting AI systems and the infrastructure they run on. Day to day, you architect and optimize infrastructure components, write and review code and deployment scripts, design and tune cloud and on-premises compute resources such as GPU clusters and distributed training environments, deploy AI systems and models into production, and build and optimize data pipelines that feed AI and ML workflows. You optimize the computational stack for performance, cost, power, and scalability, monitor AI systems and infrastructure health across both InfraOps and MLOps disciplines, perform AI monitoring to track model and system performance, and independently troubleshoot and resolve complex issues across the stack. You also mentor junior engineers, contribute to architectural decisions, and help establish best practices. This is a hands-on, ownership-driven where you apply and deepen your expertise across modern tools and platforms &mdash; including container orchestration, model serving, CI/CD pipelines, InfraOps, MLOps, and AI monitoring &mdash; while making meaningful contributions to infrastructure that enables AI-driven business outcomes.</p><p></p><p><b>
THE WORK</b></p><ul><li>
Write, review, and debug code, scripts, and infrastructure-as-code for AI infrastructure, automation, and tooling, setting standards for quality across the team.</li><li>
Architect, configure, and provision compute resources across cloud and on-premises environments, including GPU clusters and distributed training setups, optimizing for performance and utilization.</li><li>
Design and maintain deployment automation and CI/CD pipelines to support reliable, repeatable releases of AI systems, models, and applications.</li><li>
Deploy AI systems, models, and data pipelines into production, defining and improving the processes and best practices others follow.</li><li>
Lead container orchestration and model serving using tools such as Docker, Kubernetes, and model deployment frameworks.</li><li>
Architect and optimize the computational stack for performance, power, cost, and scalability, balancing trade-offs against business goals.</li><li>
Evaluate and select tools, frameworks, and platforms, making recommendations that shape the infrastructure roadmap.</li><li>
Integrate AI models and systems into existing enterprise systems, ensuring interoperability, security, and regulatory compliance.</li><li>
Own AI monitoring and infrastructure health across InfraOps and MLOps, tracking performance, reliability, and utilization, and driving remediation.</li><li>
Independently troubleshoot and resolve complex issues across the computational stack &mdash; hardware, networking, software, and models &mdash; and lead root-cause analysis.</li><li>
Mentor junior engineers and lead code reviews, providing technical direction and supporting their growth.</li><li>
Define and document architecture standards, processes, and procedures, and apply security, cost-efficiency, and scalability best practices across the infrastructure.</li></ul></div>
<br>
<div><p><b>EDUCATION</b></p><ul><li>
Bachelor's Degree in Computer Science, Computer Engineering, related Engineering field</li></ul><p></p><p><b>
BASIC (REQUIRED) QUALIFICATION</b></p><ul><li>
Experienced with coding, building, monitoring, troubleshooting applications of AI/ML models; selecting, designing and infrastructure for deploying and running them on premise or on public cloud.</li><li>
Strong understanding of AI and machine learning as a subject.</li><li>
Strong understanding of computing infrastructure a subject, preferred knowledge of AI infrastructure.</li><li>
Proficient in programming languages such as Python, Java, or C++.</li><li>
Experience with data pipeline and workflow management tools (e.g., Apache Airflow, Kubeflow).</li><li>
Strong problem-solving skills and ability to work in a fast-paced environment.</li><li>
Excellent communication and collaboration skills.</li><li>
Experience in AI/ML infrastructure engineering or related roles on a hyperscaler platform for deploying large scale solutions.</li></ul></div>

AI Infrastructure Architecture Specialist

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