At a Glance
- Tasks: Lead the design and evolution of AI architecture, shaping standards and strategies for innovative solutions.
- Company: Equinor, a forward-thinking company committed to diversity and innovation.
- Benefits: Competitive salary, global parental leave, bonuses, and flexible work arrangements.
- Other info: Join a diverse team with excellent career growth opportunities and a supportive culture.
- Why this job: Make a real impact in AI while mentoring others and driving cutting-edge technology.
- Qualifications: Master’s or PhD in relevant fields with strong leadership and technical skills.
The predicted salary is between 80000 - 100000 £ per year.
Responsibilities
- Define and evolve the enterprise reference architecture for agentic and generative AI, establishing standards, decision principles, and guardrails that will shape how these capabilities scale across Equinor.
- Partner with AI and ML engineering teams to deliver production‑grade agentic systems: orchestration, grounded retrieval, structured LLM integrations with enterprise APIs, MCP‑based tool/data access, and multimodal document understanding.
- Lead solution strategy, technology choices, and architectural blueprints; align senior stakeholders, engineering teams, and strategic partners; and provide technical leadership from early concept through scaled deployment.
- Embed safety, compliance, and privacy by design; align with GDPR and the EU AI Act; enforce policy as code and safe tool execution; manage uncertainty in non‑deterministic systems by surfacing confidence, bounding autonomy, routing to human oversight, and providing safe fallback and rollback paths.
- Raise engineering quality and long‑term capability by driving performance, reliability, and cost efficiency while mentoring others and building reusable foundations for future AI solutions.
Required Qualifications
- Master’s or PhD in Computer Science, Data Science, Machine Learning, Linguistics, or related field.
- Deep architectural experience across data, model, and application layers, with strong judgment on trade‑offs, scalability, risk, and compliance in enterprise AI systems.
- Proven leadership in navigating ambiguity, shaping technical direction, aligning senior stakeholders, and translating AI strategy into business‑aligned execution.
- Hands‑on experience with modern LLMs and agent frameworks (e.g., LangGraph, AutoGen, LangChain/LlamaIndex, Semantic Kernel).
- NLP and generative AI expertise, including prompt design, RAG architectures, model evaluation, and practical experience with major LLM providers and open‑source models.
- Solid Python and software engineering fundamentals (testing, CI/CD, version control).
- A strong track record of delivering end‑to‑end AI solutions from concept to measurable business value.
Preferred Qualifications
- Recognized thought leadership through mentoring, publishing, speaking, patents, or stewardship of influential open‑source initiatives.
- Multimodal AI: document and image understanding, diagram Q&A, speech‑to‑text (e.g., Whisper).
- Responsible AI: PII handling, red‑teaming, content moderation, risk assessment, regulatory compliance.
- Containers and cloud: Docker, Kubernetes; Azure (Azure ML, AKS, Azure OpenAI, storage, networking).
- Enterprise integration: APIs, events/messaging, standardised data and tool access via MCP.
Benefits
- Comprehensive benefits package with competitive salary, global parental leave, bonus scheme and pension plan.
- Development opportunities: learning activities, internal job market for career growth across disciplines and geographies.
- Flexible work arrangements and work‑life balance support.
- Inclusive culture encouraging diversity, belonging, and respect.
Equal Opportunities
Equinor is an equal‑opportunity employer. We make all employment decisions without regard to race, colour, religion, sex, sexual orientation, gender identity, national origin, age, disability, marital status, parental status, veteran status, or any other protected status. Reasonable adjustments will be made during the recruitment process for candidates with disabilities or long‑term health conditions.
Sr. Manager / Lead Architect Agentic and Generative AI in London employer: 1200 Equinor ASA
Equinor is an exceptional employer, offering a dynamic work environment that fosters innovation in agentic and generative AI. With a comprehensive benefits package, flexible work arrangements, and a strong commitment to employee development, we empower our team members to grow their careers while maintaining a healthy work-life balance. Our inclusive culture prioritises diversity and respect, making Equinor a rewarding place for talented individuals to contribute to cutting-edge technology in a supportive setting.
StudySmarter Expert Advice🤫
We think this is how you could land Sr. Manager / Lead Architect Agentic and Generative AI in London
✨Network Like a Pro
Get out there and connect with folks in the industry! Attend meetups, webinars, or conferences related to AI and architecture. You never know who might have the inside scoop on job openings or can put in a good word for you.
✨Show Off Your Skills
When you get the chance to chat with potential employers, don’t hold back! Share your hands-on experience with LLMs and agent frameworks. Talk about your past projects and how you’ve tackled challenges in AI systems – this is your time to shine!
✨Tailor Your Approach
Make sure you’re aligning your discussions with the company’s goals and values. Research Equinor’s projects and mention how your expertise in generative AI can help them achieve their objectives. It shows you’re genuinely interested and invested!
✨Apply Through Our Website
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re proactive and serious about joining the team at Equinor.
We think you need these skills to ace Sr. Manager / Lead Architect Agentic and Generative AI in London
Some tips for your application 🫡
Tailor Your Application:Make sure to customise your CV and cover letter to highlight your experience with agentic and generative AI. We want to see how your skills align with the responsibilities outlined in the job description, so don’t hold back on showcasing your relevant projects!
Showcase Your Leadership Skills:Since this role involves leading teams and aligning stakeholders, it’s crucial to demonstrate your leadership experience. Share specific examples of how you've navigated ambiguity and shaped technical direction in past roles. We love seeing how you’ve made an impact!
Highlight Technical Expertise:Don’t forget to emphasise your hands-on experience with modern LLMs and agent frameworks. Mention any relevant projects or technologies you’ve worked with, especially those that relate to the preferred qualifications. This is your chance to shine!
Apply Through Our Website:We encourage you to submit your application through our website for a smoother process. It helps us keep track of your application and ensures you’re considered for the role. Plus, it’s super easy to do!
How to prepare for a job interview at 1200 Equinor ASA
✨Know Your Architecture Inside Out
Make sure you have a solid grasp of enterprise reference architecture, especially in the context of agentic and generative AI. Be prepared to discuss how you've defined standards and decision principles in your previous roles, as this will show your depth of knowledge and experience.
✨Showcase Your Technical Leadership
Highlight your experience in leading solution strategies and aligning stakeholders. Prepare examples where you've successfully navigated ambiguity and translated AI strategies into actionable plans. This will demonstrate your ability to lead from concept through to deployment.
✨Demonstrate Hands-On Experience
Be ready to talk about your practical experience with modern LLMs and agent frameworks. Discuss specific projects where you've implemented these technologies, focusing on the outcomes and business value delivered. This will help you stand out as a candidate who can bridge theory and practice.
✨Emphasise Responsible AI Practices
Given the importance of safety, compliance, and privacy in AI, prepare to discuss how you've embedded these principles in your work. Share examples of how you've handled PII, conducted risk assessments, or ensured regulatory compliance, showcasing your commitment to responsible AI development.
