ai engineering manager

National Bank of Bahrain

<div>
 
 
 Job Purpose
 
 
 
 
 
 
 The AI Engineering Manager is responsible for designing, building, integrating, and operationalizing Artificial Intelligence capabilities across the Bank. The role leads the technical implementation of AI platforms, AI services, Agentic AI solutions, Generative AI applications, and the NBB Decision Intelligence Platform (NDIP). The role holder will work closely with Enterprise Architecture, Data Engineering, Application Engineering, Cyber Security, Risk, Compliance, and business stakeholders to establish scalable, secure, and governed AI capabilities. The role will be responsible for AI engineering standards, AI platform development, AI solution integration, AI orchestration frameworks, Human-in-the-Loop controls, and AI operationalization.
 
 
 
 
 
 
 Key Responsibilities
 
 
 
 
 
 
 
 AI Engineering &amp; Platform Development
 
 
 <ul>
 <li>
 Lead the design and implementation of AI platforms and services across the Bank.
 </li>
 <li>
 Design and develop NDIP components including orchestration services, AI workflows, decision APIs, and Human-in-the-Loop capabilities.
 </li>
 <li>
 Establish AI engineering standards, reusable frameworks, and best practices.
 </li>
 <li>
 Design and develop secure APIs and microservices supporting AI-enabled business processes.
 </li>
 <li>
 Develop and maintain backend services using technologies such as Node.js and TypeScript, implementing modular services for decision APIs, case management, workflow orchestration, and audit logging.
 </li>
 <li>
 Support the implementation of workflow orchestration mechanisms to manage decision processes involving automated steps and human approvals.
 </li>
 </ul>
 
 
 
 
 
 Agentic AI &amp; Intelligent Automation
 
 
 <ul>
 <li>
 Design and implement Agentic AI solutions supporting banking use cases.
 </li>
 <li>
 Build and support the business to build AI agents capable of executing multi-step workflows and business processes.
 </li>
 <li>
 Evaluate and implement agent orchestration frameworks and emerging AI technologies.
 </li>
 <li>
 Establish Human-in-the-Loop controls, approval workflows, and governance mechanisms for autonomous and semi-autonomous AI solutions.
 </li>
 </ul>
 
 
 
 
 
 AI
 
 
 Integration &amp; Solution Enablement
 
 
 <ul>
 <li>
 Integrate AI services with enterprise platforms including Core Banking, Fraud, AML, Data Warehouse, Digital Channels, and other systems.
 </li>
 <li>
 Develop and maintain AI Gateway capabilities supporting model routing and orchestration.
 </li>
 <li>
 Implement Retrieval-Augmented Generation (RAG) and enterprise knowledge solutions.
 </li>
 <li>
 Support deployment and integration of Generative AI solutions across business functions.
 </li>
 <li>
 Integrate NDIP with enterprise AI systems including machine learning models, LLM-based services, and AI scoring engines.
 </li>
 <li>
 Assist in implementing mechanisms to capture AI outputs, confidence scores, and explainability data to ensure transparency in decision-making.
 </li>
 <li>
 Develop APIs and services for retrieving customer, transaction, and risk-related information required for decision-making.
 </li>
 <li>
 Support implementation of event-driven and API-based integrations with enterprise systems.
 </li>
 </ul>
 
 
 
 
 
 AI Infrastructure, MLOps &amp; LLMOps
 
 
 <ul>
 <li>
 Establish AI engineering environments and deployment pipelines.
 </li>
 <li>
 Implement model lifecycle management, monitoring, observability, and governance controls.
 </li>
 <li>
 Support AI platform scalability, resilience, and operational stability.
 </li>
 <li>
 Collaborate with infrastructure teams to support cloud-native AI workloads.
 </li>
 </ul>
 
 
 
 
 
 Workflow &amp; Case Management
 
 
 <ul>
 <li>
 Support the implementation of case lifecycle management including case creation, routing, escalation, review, and closure.
 </li>
 <li>
 Help ensure that decision workflows support human-in-the-loop review processes, escalation rules, and SLA monitoring.
 </li>
 <li>
 Contribute to implementing workflow processes supporting multi-step approvals and compliance requirements.
 </li>
 </ul>
 
 
 
 
 
 Platform Support &amp; Maintenance
 
 
 <ul>
 <li>
 Provide technical support for the NDIP platform, including troubleshooting issues, monitoring platform performance, and resolving defects.
 </li>
 <li>
 Assist in maintaining platform reliability, availability, and operational stability.
 </li>
 <li>
 Support system enhancements, upgrades, and performance improvements as the platform evolves.
 </li>
 </ul>
 
 
 
 
 
 Governance &amp; Audit
 
 
 <ul>
 <li>
 Assist in implementing mechanisms to maintain complete decision traceability, including decision inputs, rules triggered, AI outputs, user actions, and final outcomes.
 </li>
 <li>
 Support the implementation of audit logging and monitoring capabilities to meet regulatory and governance requirements.
 </li>
 <li>
 Work with risk and compliance teams to ensure appropriate AI and decision governance controls are embedded in the platform.
 </li>
 <li>
 Implement AI governance, traceability, and auditability controls.
 </li>
 <li>
 Implement monitoring and controls for AI outputs and decision processes.
 </li>
 </ul>
 
 
 
 
 
 Qualifications &amp; Experience
 
 
 
 
 
 <ul>
 <li>
 Bachelor&rsquo;s degree in computer science, software engineering, information technology, or a related discipline is required.
 </li>
 <li>
 Master's degree in computer science, software engineering, information technology, or a related discipline is preferred.
 </li>
 <li>
 Additional certifications or training in software engineering, cloud technologies, or AI/ML technologies are preferred.
 </li>
 <li>
 Minimum 5-6 years of experience in software engineering, platform development, or backend application development with 3 years in the same or similar function.
 </li>
 </ul>
</div>

AI Engineering Manager

<div><div><div>Entity:
Technology 
Job Family Group:
IT&amp;S Group 
Job Description:
This role leads AI engineering capability across Upstream and Downstream business domains within bp's central digital delivery organisation. The Principal AI Engineer is responsible for managing a team of AI focused software engineers, owning the end-to-end delivery of AI-powered solutions from design through to production, and contributing to the broader AI engineering strategy for the function.
The role exists to accelerate bp's adoption of applied AI by embedding technical leadership close to business domains, ensuring AI solutions are fit for purpose, scalable, and aligned with enterprise standards. As a senior leader in a growing AI capability, this individual plays a key role in shaping how AI engineering is practised across the organisation, in growing the talent pipeline for the discipline and line managing a team of high performing software engineers.
Key Accountabilities<ul><li>
Lead and develop the skills of a team of software engineers, setting technical direction, fostering a culture of engineering excellence, and ensuring the team delivers high-quality AI solutions aligned to business domain needs.</li><li>
Own the end-to-end delivery of AI engineering programmes within assigned business domains, driving definition of requirements, solution design, iterative development, and production deployment.</li><li>
Partner with business stakeholders and product managers to translate domain challenges into well-scoped AI engineering initiatives, prioritising efforts that deliver measurable business value.</li><li>
Contribute to the overall AI engineering strategy for the function, establishing and promoting practices, standards, and patterns that improve the consistency and quality of AI solutions across teams.</li><li>
Manage relationships with internal and external engineering resources, including contracted and offshore teams, ensuring delivery quality and alignment with technical standards.</li><li>
Collaborate with platform, data, and architecture teams to ensure AI solutions are built on sound foundations and integrate appropriately with the broader enterprise technology landscape.</li></ul><h1 class="jobSectionHeader">
What you will bring...</h1><ul><li>
Demonstrable experience leading and managing software or AI engineering teams in a production environment, with accountability for team performance, technical quality, and delivery outcomes.</li><li>
Strong software engineering background, including proficiency in modern programming languages and software development practices (e.g., version control, CI/CD, automated testing).</li><li>
Hands-on experience delivering AI or machine learning solutions at scale, including model development, deployment, and ongoing operations (MLOps).</li><li>
Experience with large language models (LLMs), generative AI techniques, or agentic AI frameworks applied to real-world business problems.</li><li>
Track record of managing multi-stakeholder programmes, balancing business priorities with technical constraints and engineering quality.</li><li>
Strong written and verbal communication skills, with the ability to present technical concepts clearly to non-technical partners and senior leadership.</li><li>
Bachelor's degree or higher in Computer Science, Software Engineering, Data Science, Mathematics, or a related technical subject area.</li></ul>
Desirable Criteria<ul><li>
Experience operating in the energy sector or another complex industrial or commodities environment.</li><li>
Familiarity with enterprise data platforms, SaaS integration, or data mesh/fabric architectural patterns.</li><li>
Prior exposure to AI applications in operational, trading, or engineering domains (e.g., optimisation, forecasting, natural language interfaces to enterprise data).</li><li>
Formal training or certification in AI/ML (e.g., AWS Machine Learning Specialty, Google Professional ML Engineer, or equivalent).</li></ul><h1 class="jobSectionHeader">
Why join us?</h1>
We&rsquo;re committed to supporting leaders who want to make an impact. At bp, you&rsquo;ll have the chance to shape and influence outcomes across businesses. You&rsquo;ll be part of an inclusive environment where diverse perspectives are valued, and where your contribution to performance and integration matters. We invest in the growth and wellbeing of our people, providing the resources, networks, and development opportunities needed to thrive.
Our total rewards package includes competitive pay, bonuses, share options, and a range of flexible benefits designed to meet your needs &mdash; from healthcare and retirement plans to paid time off and agile working. We recognise that people have multifaceted lives, and we strive to offer a career experience that reflects that.
Apply now!
Location
This position is based in our Sunbury office. Please note however that this will move to Southwark, London by end 2027. 
Travel Requirement
Up to 10% travel should be expected with this role 
Relocation Assistance:
This role is not eligible for relocation 
Remote Type:
This position is a hybrid of office/remote working 
Skills:
Agility core practices, Agility core practices, API and platform design, Cloud Platforms, Collaboration, Communication, Configuration management and release, Continuous deployment and release, Creating a high performing team, Database Design, Digital Project Management, Documentation and knowledge sharing, Emerging technology monitoring, Facilitation, Information Security, Mentoring, Metrics definition and instrumentation, NoSql data modelling, Problem Solving, Relational Data Modelling, Risk Management, Scripting, Secure development, Service operations and resiliency, Software Design and Development {+ 7 more} 
Legal Disclaimer:
We are an equal opportunity employer. We do not discriminate on the basis of protected characteristics like race, religion, color, sex, national origin, sexual orientation, veteran status or disability status. Individuals with an accessibility need may request an adjustment/accommodation related to bp&rsquo;s recruiting process (e.g., accessing the job application, completing required assessments, participating in telephone screenings or interviews, etc.). If you would like to request an adjustment/accommodation related to the recruitment process, please contact us. 
 
If you are selected for a position and depending upon your role, your employment may be contingent upon adherence to local policy. This may include pre-placement drug screening, medical review of physical fitness for the role, and background checks.</div>
<div>Legal Disclaimer:

We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, sex, gender, gender expression, sexual orientation, age, marital status, socioeconomic status, neurodiversity/neurocognitive functioning, veteran status or disability status. Individuals with an accessibility need may request an adjustment/accommodation related to bp&rsquo;s recruiting process (e.g., accessing the job application, completing required assessments, participating in telephone screenings or interviews, etc.). If you would like to request an adjustment/accommodation related to the recruitment process, please contact us.

If you are selected for a position and depending upon your role, your employment may be contingent upon adherence to local policy. This may include pre-placement drug screening, medical review of physical fitness for the role, and background checks.</div>
</div><div>Expand job description</div></div>
 <div><div>Disclaimer 


This is a high-level summary only of terms and current discretionary benefits applicable to certain roles. Some rewards, benefits and policies are at managers&rsquo; discretion and vary depending on where you work within the business. All terms subject to contract and all discretionary benefits subject to policy and eligibility.</div></div>

Principal AI Engineering Manager

Quantspark

<div>Title: Engineering Manager 
Reporting to: Head of Engineering 
Office Environment: Hybrid, Central London Office 
Type: Full time, Permanent<h2 class="jobSectionHeader"> 
About QuantSpark</h2>
QuantSpark is an award-winning AI and data consultancy, but we don't just advise, we build. We help businesses in the UK and beyond, as well as governments, apply data, analytics and AI for measurable human and societal benefit, not just profit. This means tackling real-world challenges, innovating at scale, and forging solutions that deliver real impact to our clients.
Our culture is built on meritocracy of ideas, where the best thinking wins regardless of seniority, a place where intelligent failure is treated as something to learning form, and where we seriously invest in people with opportunities for career acceleration, ownership over projects, and a personalised &pound;6K per year L&amp;D budget. We&rsquo;ve recently been named as finalist in the Culture 100 Awards, shortlisted from more than 5,200 UK companies, with 93% of our team rating their experience here positively in May 2026.<h2 class="jobSectionHeader"> 
Our Client Portfolio</h2>
We work with prestigious, high-growth organisations and sector leaders, in the UK and internationally:<ul><li>Financial Services &amp; Private Equity: Delivering AI-powered analytics, risk, and operational tools.</li><li>Retail &amp; Consumer Brands: Optimising pricing, inventory, and engagement through actionable analytics.</li><li>Asset Management: Developing investment infrastructure and automated risk management systems.</li><li>Public Sector: Trusted by government departments for fraud analytics, predictive maintenance, and operations optimisation.</li><li>SaaS &amp; Manufacturing: Driving technological transformation and efficiency across verticals.</li></ul><h2 class="jobSectionHeader"> 
The Role</h2>
As Engineering Manager, you'll lead a team of 4 Data Engineers, 1 AI Engineer and 1 QA, and sit on the wider management team. A good portion of your week will be the coaching and line-managing of that team, growing people, unblocking them and holding the bar on quality. The rest will be spent delivering across a mix of client engagements and our own product development. This is a player-coach role, not pure people management, you'll stay hands-on enough to make architectural calls, review code and step in on the hard problems when needed.
Using AI well is core to the job, knowing where it genuinely adds value, where it doesn't, and how to embed it sensibly into how your team delivers and what you build for clients, without cutting corners on quality, security or judgement.<ul><li>Oversee and architect delivery of multiple software and data projects, ensuring scalability, security, and maintainability.</li><li>Guide and mentor engineers from junior to senior level, fostering technical growth and a high-performance culture.</li><li>Champion the practical, responsible adoption of AI across engineering workflows, tooling, and client solutions.</li><li>Partner with product managers and technical leads on deliverables, resourcing, and timelines.</li><li>Drive innovation in engineering processes, promoting best practices, DevOps, and technical standards.</li><li>Operate calmly between competing priorities, making clear trade-offs across delivery, people, and quality.</li><li>Engage with client stakeholders, managing partnerships and ensuring solutions are adopted.</li></ul> 
You Should Hit the Apply Button If
We're a lean consultancy scaling deliberately. A lot of what you'd take for granted at a larger firm is still yours to build such as engineering standards, delivery processes, tooling, the shape of the team itself. We move fast, we take on hard problems that often the bigger consultancies haven&rsquo;t been able to solve. You will have real autonomy and a genuine say in how engineering works at QuantSpark, but you'll also be building the road as you drive it. That calls for someone comfortable with ambiguity, willing to make the call on imperfect information, and is ready to get hands on, helping to build the organisation.<ul><li>You excel at managing teams, understand 'culture add' and how to inspire and coach a team to do their best work.</li><li>You bring hands-on experience across software and data &mdash; for example Python (Flask/Django), React.js, and analytics/data engineering (building pipelines, models, and data products).</li><li>You're fluent in software and data architecture, containerisation, and cloud platforms (AWS/Azure).</li><li>You understand the value of AI and know how to use it wisely, helping your team pick the right tools for the right problems.</li><li>You've managed cross-functional teams, mentored engineers, and championed technical and professional growth.</li><li>You can hold competing priorities at once and still keep a team focused, motivated, and performing.</li><li>You're passionate about DevOps and modern tooling, continuously pushing on process and code quality.</li></ul> 
I Want to Work for a Company That<ul><li>Balances visionary leadership with hands-on technical impact.</li><li>Prioritises impactful work and an innovative culture.</li><li>Treats AI as a tool to be used thoughtfully, not a box to be ticked.</li><li>Builds solutions that create lasting impact in both business and society.</li></ul> 
I'm Looking to Work With<ul><li>Smart, collaborative, cross-disciplinary teams solving complex business and technical problems.</li><li>Partners and clients who value AI and data-driven transformation.</li><li>Leadership that inspires, trusts, and invests in emerging talent.</li></ul> 
In 3&ndash;5 Years I Want to Be<ul><li>Recognised for delivering impactful work that matters to clients and the business.</li><li>A recognised mentor who's grown talented engineers and future leaders.</li><li>An influential leader connecting strategic decisions with the smart use of technology and AI.</li></ul><h2 class="jobSectionHeader"> 
Perks &amp; Benefits</h2><ul><li>&pound;6,000 annual training/conference allowance</li><li>Matched pension contributions up to 6%</li><li>Private Healthcare (Vitality)</li><li>EMI share options&mdash;own a part of QuantSpark&rsquo;s growth</li><li>Work abroad up to one month every year</li><li>25 days annual leave (+ bank holidays with the option to buy/sell up to 5 days)</li><li>Annual volunteering day</li><li>Cycle-to-work scheme</li><li>Central London office with socials &amp; events</li><li>Discounts with major retailers, tech, fitness, travel partners</li></ul><h2 class="jobSectionHeader"> 
Equal Opportunities</h2>
We are committed to building a diverse and inclusive team. Different perspectives, identities, and experiences make us stronger&mdash;both as people and as a business. All qualified applicants will be considered regardless of sex, sexual orientation, marital status, race, nationality, religion, disability, or age.</div>

Engineering Manager

Bellrock Group

<div>
 
 Based in either Leicester or London, with hybrid (home/office) working.
 
 
 
 The AI Engineering Lead is a senior technical role at the heart of Bellrock's internal AI capability. You will own the engineering architecture that turns AI ideas and use cases into production-ready systems. Working closely with the Head of AI and a team of AI Graduates, you will design, build, and operate the technical infrastructure that powers AI across our internal operations. This is a hands-on leadership role &mdash; you will be the most senior technical voice in the internal AI team, making critical decisions about tooling, integrations, security boundaries, and architecture, while also mentoring graduates and guiding delivery.
 
 
 
 Key Responsibilities
 
 
 
 <ul>
 <li>
 Own the technical architecture for Bellrock's internal AI systems, including agentic workflows, automation pipelines, and integrations with internal platforms and data sources.
 </li>
 <li>
 Lead the engineering build of AI use cases from prototype to production, ensuring solutions are robust, secure, and maintainable.
 </li>
 <li>
 Define and enforce engineering standards, including data handling, model access, API integration, prompt engineering, and tool use boundaries.
 </li>
 <li>
 Evaluate and select appropriate AI tooling, platforms, and frameworks, with a pragmatic focus on foundation model APIs, orchestration layers, and integration patterns.
 </li>
 <li>
 Collaborate closely with the AI Delivery Manager to translate scoped use cases into technical delivery plans with clear milestones.
 </li>
 <li>
 Act as a senior technical counterpart to the Head of AI on governance and risk matters &mdash; contributing to the AI risk assessment process, supporting data residency compliance, and advising on agentic AI safeguards such as least privilege, reversibility, and kill-switch mechanisms.
 </li>
 <li>
 Mentor and technically develop a team of AI Graduate Analysts, broadening their engineering thinking and hands-on capability.
 </li>
 <li>
 Stay current with the rapidly evolving AI engineering landscape and bring relevant innovations into Bellrock's internal practice.
 
 
 </li>
 </ul>
 
 Skills &amp; Experience
 
 
 
 <ul>
 <li>
 Proven experience building and deploying AI-powered applications using foundation model APIs (e.g. Anthropic Claude, OpenAI, Azure, AWS).
 </li>
 <li>
 Strong proficiency in Python and/or JavaScript/TypeScript; experience with agentic frameworks and orchestration tools (e.g. LangChain, LlamaIndex, or equivalent).
 </li>
 <li>
 Hands-on experience integrating AI systems with enterprise platforms, APIs, and data pipelines.
 </li>
 <li>
 Solid understanding of prompt engineering, RAG (retrieval-augmented generation), and tool/function calling patterns.
 </li>
 <li>
 Experience working within information security and data governance constraints, including an understanding of data residency and access control principles.
 </li>
 <li>
 Excellent communication skills, be able to explain technical architecture to non-technical stakeholders and translate business requirements into engineering decisions.
 </li>
 <li>
 Experience mentoring junior engineers or analysts.
 </li>
 <li>
 Familiarity with MCP (Model Context Protocol) or similar tool-use frameworks is desirable but not essential.
 </li>
 <li>
 You drive AI use cases from approved scope to production reliably and securely, you make things happen.
 </li>
 <li>
 You build coherent, well-documented technical architectures that scale as the use case pipeline grows.
 </li>
 <li>
 You develop others, Graduate Analysts in your team grow their engineering thinking and build with greater confidence and rigour under your guidance.
 </li>
 <li>
 You operate with integrity: AI systems you build consistently respect agreed governance, data handling, and security boundaries.
 </li>
 <li>
 You thrive with autonomy and take ownership of hard technical decisions, while staying collaborative and clearly communicating your reasoning.
 
 
 </li>
 </ul>
 
 AI fluency &amp; learning mindset: We are looking for people who actively use AI in their day‑to‑day work, demonstrate strong curiosity about new technologies, and take ownership for continuously improving how they think, work, and deliver.
 
 
 
 
 Working arrangements
 
 
 
 We embrace smarter working practices which offer our employees the opportunity to work their hours flexibly and remotely where their roles and business needs allow. In this role, we are open to the successful candidate being based from the Leicester or London office on a hybrid basis (this is not a dual office role).
 
 
 
 What can we offer you?
 
 
 
 Upon joining Bellrock, you can expect a comprehensive benefits package including:
 
 
 25 days annual leave plus bank holidays + 1 additional day as a thank you (enjoy it, it&rsquo;s on us)
 
 
 Salary exchange pension scheme
 
 
 Life cover
 
 
 Paid sick leave
 
 
 Health Assured employee assistance and wellness program
 
 
 Enhanced maternity, paternity and adoption leave
 
 
 Salary sacrifice schemes: Cycle to work
 
 
 Holiday purchase scheme of additional 5 days per year
 
 
 Offers and discount scheme designed to save money on everyday shopping and essentials
 
 
 Healthcare Cashplan
 
 
 MotorSave Scheme
 
 
 Refer a friend
 
 
 Liftshare
 
 
 Virtual GP
 
 
 
 Why Bellrock?
 
 
 
 Our people are our passion, so we&rsquo;re all about helping them to achieve their ambitions. That means putting everything in place for you to have a rewarding career with us. So you can go far in your career, with us behind you. And our business will grow, too. So, if you&rsquo;re ready to start your career journey with Bellrock we&rsquo;re ready to welcome you. It&rsquo;s a great place to be.
 
 
 We would like to attract talent from all corners of the world for this role. Or commitment is to an equitable recruitment process so feel free to apply in any way that suits you. We are looking for the right person, not necessarily just the right person for this role
 
 
 Apply today.
</div>

AI Engineering Lead

MYLO

<div>Role Overview
We are seeking an experienced Engineering Manager &ndash; Data Science to lead a high-performing Data Science squad responsible for delivering scalable machine learning solutions, predictive models, and AI-driven products that drive business impact.
The ideal candidate combines deep technical expertise in Data Science and Machine Learning with strong people leadership capabilities. This role requires a strategic thinker who can manage a multidisciplinary squad, define technical roadmaps, mentor engineers and data scientists, and collaborate closely with Product, Engineering, Analytics, and Business stakeholders.
Key ResponsibilitiesLeadership &amp; Team Management<ul><li>
Lead, coach, and develop a squad of Data Scientists, Machine Learning Engineers.</li><li>
Drive team performance through goal setting, mentoring, career development, and continuous feedback.</li><li>
Build and foster a culture of innovation, ownership, collaboration, and technical excellence.</li><li>
Support recruitment, onboarding, and talent development initiatives.</li><li>
Manage squad capacity, planning, and execution to ensure successful delivery of strategic projects.</li></ul>
Technical Leadership<ul><li>
Define and execute the Data Science roadmap aligned with business objectives.</li><li>
Lead the design, development, deployment, and monitoring of machine learning models and AI solutions.</li><li>
Establish engineering best practices for model development, experimentation, MLOps, and production deployment.</li><li>
Guide architectural decisions related to data platforms, machine learning infrastructure, and AI systems.</li><li>
Ensure scalability, reliability, and maintainability of Data Science solutions.</li></ul>
Stakeholder Management<ul><li>
Partner with Product Managers, Engineering Leaders, and Business stakeholders to identify opportunities for data-driven decision making.</li><li>
Translate complex business problems into analytical and machine learning solutions.</li><li>
Communicate technical findings and recommendations to both technical and non-technical audiences.</li><li>
Drive alignment across cross-functional teams to deliver measurable business outcomes.</li></ul>
Delivery &amp; Execution<ul><li>
Oversee end-to-end project delivery from discovery and experimentation to production deployment.</li><li>
Monitor KPIs and model performance to ensure continuous improvement.</li><li>
Balance technical debt, innovation, and business priorities effectively.</li><li>
Drive agile delivery practices within the squad.</li></ul> 

Requirements 
<ul><li>
10+ years of experience in Data Science, Machine Learning, Software Engineering, or related technical fields.</li><li>
4+ years of people management experience leading Data Science or Machine Learning teams.</li><li>
Proven experience leading cross-functional squads in product-driven environments.</li><li>
Demonstrated track record of deploying machine learning models into production.</li></ul>
Technical Skills
Strong expertise in:
<ul><li><ul><li>Machine Learning</li><li>
Statistical Modeling</li><li>
Predictive Analytics</li><li>
Deep Learning</li><li>
NLP and/or Generative AI</li><li>
Experiment Design and A/B Testing</li></ul></li></ul>
Advanced proficiency in:
<ul><li><ul><li>Python</li><li>
SQL</li><li>
Data Visualization tools</li></ul></li></ul>
Experience with:
<ul><li><ul><li>MLOps practices</li><li>
Model monitoring and governance</li><li>
Cloud platforms (Azure, AWS, or GCP)</li><li>
Data Engineering concepts and modern data platforms</li></ul></li></ul>
Familiarity with:
<ul><li><ul><li>LLMs and Generative AI applications</li><li>
Feature stores</li><li>
Recommendation systems</li><li>
Real-time machine learning solutions</li></ul></li></ul>
Preferred Qualifications<ul><li>
Master's degree in Computer Science, Data Science, Artificial Intelligence, Statistics, Mathematics, or a related field.</li><li>
Experience within FinTech, Digital Products, E-commerce, Banking, or Technology organizations.</li><li>
Experience managing large-scale data platforms and AI initiatives.</li><li>
Knowledge of modern software engineering practices and DevOps methodologies.</li></ul> 

Benefits 
<ul><li>
Lead cutting-edge AI and Data Science initiatives.</li><li>
Build products impacting millions of users.</li><li>
Work with highly talented engineering and product teams.</li></ul><ul><li>
Shape the future of data-driven decision making within the organization.
</li><li>When you come to our b_labs office, you'll find creative workspaces and an open design to foster collaboration between teams.
</li><li>You know best whether you want to work from home or in the office.
</li><li>From &quot;Day 1&quot; you will receive all the equipment you need be successful at work.</li></ul></div>

Engineering Manager (Data Science)

NVIDIA

<div><div><div>At NVIDIA, we aren't just powering the AI revolution&mdash;we're accelerating it. We are accelerating LLM inference across the stack and across all open source LLM frameworks like TensorRT LLM, vLLM and SGLang. With demand for AI exploding, particularly in the realm of large language models (LLMs) and vision language models (VLMs, VLAs), we are significantly expanding our team.</div><div> 
We're seeking a highly skilled and driven Engineering Manager to take the lead in accelerating the next generation of LLM/VLM/VLA inference software technologies that will define the future of AI. This is a high-impact, hands-on leadership role at the intersection of deep technical expertise and world-class management. You won't just manage; you'll architect and guide a brilliant team of engineers who are pushing the performance of LLM inference. Your work will be highly collaborative, interfacing directly with NVIDIA Researchers, GPU Architects, and other teams across the company to ensure we ship production-grade, lightning-fast software that sets the global standard for AI performance.</div><div> 
What You&rsquo;ll Be Doing:</div><div><ul><li>
Lead and grow a team responsible for pushing the performance of LLM inference across multiple LLM frameworks, including TensorRT LLM, vLLM, SGLang and Dynamo on our datacenter products.</li><li>
Drive the design, implementation and optimization of features that are key to performance in LLM inference.</li><li>
Continuously improve the performance of LLM inference on current and upcoming NVIDIA datacenter architectures and GPUs.</li><li>
Continuously improve the performance of LLM inference of important foundation models.</li><li>
Work with inference benchmark teams to help tune performance for key workloads.</li><li>
Integrating cutting-edge technologies developed at NVIDIA and offering an intuitive developer experience for LLM deployment.</li><li>
Lead software development execution, with responsibility for project planning, milestone delivery, and cross-functional coordination.</li></ul></div><div>
What We Need to See:</div><div><ul><li>
MS, PhD, or equivalent experience in Computer Science, Computer Engineering, AI, or a related technical field.</li><li>
7+ overall years of overall software engineering experience, including 3+ years of technical leadership experience.</li><li>
Proven ability to lead and scale high-performing engineering teams, especially across distributed and cross-functional groups.</li><li>
Strong background in C++ or Python, with expertise in software design and delivering production-quality software libraries.</li><li>
Demonstrated expertise in large language models (LLM) and/or vision language models (VLM) and/or inference in general.</li></ul></div></div><div><div>
Ways to Stand Out from the Crowd:</div><div><ul><li>
Deep understanding of GPU architecture, CUDA programming, and system-level performance tuning.</li><li>
Background in LLM inference or working with frameworks such as TensorRT-LLM, vLLM, or SGLang.</li><li>
Passion for building scalable, user-friendly APIs and enabling developers in the AI ecosystem.</li><li>
Have a proven track record of growing and managing a team that encourages idea sharing, empowers team members, and provides opportunities for professional growth.</li></ul></div></div>
#LI-Hybrid
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 224,000 USD - 356,500 USD for Level 3, and 272,000 USD - 431,250 USD for Level 4.<div><div><div><div><div><div><div>
You will also be eligible for equity and benefits.</div></div></div></div></div></div></div>
Applications for this job will be accepted at least until June 27, 2026.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.</div>

Engineering Manager, LLM Performance

Google

<div>Applicants in San Francisco: Qualified applications with arrest or conviction records will be considered for employment in accordance with the San Francisco Fair Chance Ordinance for Employers and the California Fair Chance Act.<h3 class="jobSectionHeader">
Minimum qualifications:</h3><ul>
<li>Bachelor&rsquo;s degree or equivalent practical experience. 
</li>
<li>8 years of experience with software development. 
</li>
<li>7 years of experience leading technical project strategy, ML design, and optimizing ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).</li>
<li>5 years of experience in a technical leadership role.</li>
<li>5 years of experience in a people management or team leadership role.</li>
<li>2 years of experience with GenAI techniques (e.g., LLMs, Multi-Modal etc.) or with GenAI-related concepts.</li></ul> 
<h3 class="jobSectionHeader">
Preferred qualifications:</h3><ul>
<li>Master&rsquo;s degree or PhD in Engineering, Computer Science, or a related technical field. 
</li>
<li>5 years of experience working in a complex, matrixed organization. 
</li>
<li>Experience in building and deploying Agentic AI systems.</li>
<li>Experience in security domains.</li>
</ul><div><h2 class="jobSectionHeader">About the job</h2>
Like Google's own ambitions, the work of a Software Engineer goes beyond just Search. Software Engineering Managers have not only the technical expertise to take on and provide technical leadership to major projects, but also manage a team of Engineers. You not only optimize your own code but make sure Engineers are able to optimize theirs. As a Software Engineering Manager you manage your project goals, contribute to product strategy and help develop your team. Teams work all across the company, in areas such as information retrieval, artificial intelligence, natural language processing, distributed computing, large-scale system design, networking, security, data compression, user interface design; the list goes on and is growing every day. Operating with scale and speed, our exceptional software engineers are just getting started - and as a manager, you guide the way. 
 
With technical and leadership expertise, you manage engineers across multiple teams and locations, a large product budget and oversee the deployment of large-scale projects across multiple sites internationally. 

Our team is at the forefront of revolutionizing Google Security Operations (SecOps) through the power of artificial intelligence. We are developing a Security Agentic Platform to enable the development of first-party and third-party security agents to deliver a proactive, intelligent, and automated Agentic Security Operations Center (SoC).
 
 
In this role, you will lead a team of talented engineers in building the next generation of Security Agentic AI platforms and systems that will protect major organizations worldwide.
Google Cloud accelerates every organization&rsquo;s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google&rsquo;s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
 
 
US: $262000 - $365000 (USD) + 25% bonus target + equity + benefits 
 
Learn more about benefits at Google.</div><div><h2 class="jobSectionHeader">
Responsibilities</h2><ul>
<li>Guide, mentor, and grow a team of engineers focused on developing and deploying agentic AI for security that will power the Google Unified Security products.</li>
<li>Manage the technical goal and strategy for the Security Agentic AI, ensuring alignment with the broader security teams.</li>
<li>Collaborate with cross-functional engineering teams along with product management, data science, and security engineering to define product requirements and roadmaps, and deliver features.</li>
<li>Oversee the end-to-end development lifecycle, from ideation and design to implementation, testing, and deployment of AI-driven agentic security solutions.</li>
<li>Foster a culture of innovation and continuous improvement, staying abreast of the latest advancements in AI, machine learning, and cybersecurity.</li>
</ul></div>Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.</div>

Senior Software Engineering Manager, Agentic Platform, Cloud Security

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