Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Lead AI delivery programs and design multi-agent systems for global clients.
- Company: Join Zensar, a leader in digital solutions and technology services.
- Benefits: Competitive salary, recognition for your impact, and a supportive team culture.
- Why this job: Make a real difference in AI while working with cutting-edge technologies.
- Qualifications: Experience in building production-ready multi-agent AI systems and strong coding skills.
- Other info: Mentorship opportunities and a dynamic environment for career growth.
The predicted salary is between 80000 - 100000 £ per year.
Zensar is a leading digital solutions and technology services company that specialises in partnering with global organisations across industries in their Digital Transformation journey. Zensar's Return on Digital strategy has enabled customers to look beyond current investments towards realising visible business benefits in their digital transformation journey.
This is not a slide-making or prompt-engineering role. We are looking for someone who has built multi-agent AI systems that run in production - not demos, not pilots that died after a sprint. You will anchor AI delivery programs end-to-end, work directly with global clients, and stay sharp on a field that changes every few weeks. You will report into and replicate the function of a senior AI delivery leader - which means you need both the depth to architect solutions and the presence to walk a CXO through what you built and why it works.
Duties and Responsibilities
- Delivery & Architecture
- Own end-to-end delivery of AI-native programs - from architecture through production deployment
- Design and build multi-agent orchestration systems using LangChain, LangGraph, CrewAI, or equivalent
- Integrate agent systems with enterprise surfaces: APIs, ERPs, CRMs, data platforms - not toy datasets
- Define agent topology: tool routing, memory strategy, state machines, fallback handling
- Agentic Coding & Development
- Run agentic coding workflows using Claude Code, Cursor, OpenAI Codex, or equivalent CLI tools
- Lead projects where AI writes significant portions of the codebase - and you guide, review, and ship it
- Work with CLAUDE.md, shared context frameworks, and multi-session agent setups for team use
- Debug non-deterministic agent outputs systematically - not by gut feel
- Client & Stakeholder Engagement
- Translate business problems into agent architectures for global CXO-level stakeholders
- Run discovery workshops, solution reviews, and delivery cadences with client teams
- Prepare and present technical proposals, POC plans, and roadmaps - own the story end-to-end
- Team & Practice
- Mentor junior AI engineers; raise AI engineering quality across the delivery team
- Stay current: evaluate new models, frameworks, and tooling before the hype catches up
- Contribute to internal knowledge bases, reusable frameworks, and accelerators
Technical Skills Required
- Proven experience of:
- Agent Orchestration: LangChain, LangGraph, CrewAI - not just conceptual
- Agentic Coding Tools: Claude Code CLI, Cursor, OpenAI Codex, Copilot
- RAG & Vector Stores: Chroma, Weaviate, Pinecone, know where RAG breaks
- LLM APIs & SDKs: Anthropic, OpenAI, Gemini - prompt design, tool use
- Python / TypeScript: Primary languages for agent + backend development
- LangSmith / Observability: Tracing, evaluation, debugging agent runs
- Cloud Platforms: Azure, AWS, GCP (at least one) - deployment, infra, managed services
- API & System Integration: REST, gRPC, Kafka - enterprise integration patterns
- MCP / Shared Context: Model Context Protocol, CLAUDE.md, Beads
- Agent Evaluation: Testing non-deterministic outputs, guardrails, evals
- CI/CD & DevOps: Git, containers, pipelines - agents need to ship
- Client Communication: Can present architecture to a CXO without jargon
Must have:
- Deployed 23 agent-based systems in production - stateful, multi-step, real users
- Used LangGraph for multi-agent orchestration with memory, tool routing, and state management
- Built projects where AI (Claude Code, Codex, Cursor) wrote significant portions of the code
- Implemented RAG pipelines end-to-end - chunking, embedding, retrieval, re-ranking, evaluation
- Integrated agents with real enterprise APIs - not just OpenAI playground or sample data
- Debugged a production agent failure - and fixed it without blaming the model
- Can articulate when NOT to use agents - that is how we know you have built things
Bonus - Real Differentiators
- Experience with Claude Code CLI in team environments (CLAUDE.md, shared context, multi-session flows)
- Familiarity with LangSmith for agent tracing, evaluation pipelines, and debugging at scale
- Has shipped something using MCP (Model Context Protocol) or similar shared-context tooling
- QA/testing mindset for agents - systematic evaluation of non-deterministic outputs
- Background in IT services or consulting - managing client expectations while building
- Experience with SLMs, fine-tuning, or on-device/edge agent deployment
Qualification: Must be educated to at least degree level or equivalent.
AI Lead in Luton employer: Zensar Technologies
Contact Detail:
Zensar Technologies Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land AI Lead in Luton
✨Tip Number 1
Network like a pro! Get out there and connect with people in the industry. Attend meetups, webinars, or conferences related to AI and digital transformation. You never know who might have the inside scoop on job openings or can put in a good word for you.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your past projects, especially those involving multi-agent AI systems. This will give potential employers a clear idea of what you can bring to the table and how you can contribute to their digital transformation journey.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. Be ready to discuss your experience with agent orchestration and coding tools. Practice explaining complex concepts in simple terms, as you'll need to communicate effectively with CXO-level stakeholders.
✨Tip Number 4
Don't forget to apply through our website! We love seeing candidates who are genuinely interested in joining us at StudySmarter. Tailor your application to highlight your relevant experience and how it aligns with our mission to help others realise their full potential.
We think you need these skills to ace AI Lead in Luton
Some tips for your application 🫡
Show Your Experience: When you're writing your application, make sure to highlight your hands-on experience with multi-agent AI systems. We want to see real examples of what you've built and how it’s been deployed in production, not just theory.
Be Clear and Concise: Keep your application straightforward and to the point. Use clear language to explain your technical skills and how they relate to the role. We appreciate a well-structured application that gets straight to the heart of your qualifications.
Tailor Your Application: Make sure to tailor your application to our job description. Highlight specific experiences that align with the duties and responsibilities we’ve outlined. This shows us you’ve done your homework and are genuinely interested in the role.
Apply Through Our Website: Don’t forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it makes the whole process smoother for everyone involved.
How to prepare for a job interview at Zensar Technologies
✨Know Your Stuff
Make sure you have a solid grasp of multi-agent AI systems and the specific tools mentioned in the job description, like LangChain and Claude Code. Be ready to discuss your past projects in detail, especially those that went live and had real users.
✨Speak Their Language
When talking to the interviewers, avoid jargon and focus on clear communication. They want to see if you can explain complex concepts to CXO-level stakeholders without losing them in technical details. Practice explaining your work in simple terms.
✨Show Your Problem-Solving Skills
Prepare to discuss how you've tackled challenges in previous projects, especially around debugging and integrating systems. They’ll be keen to hear about specific instances where you fixed production issues or made critical decisions.
✨Be a Team Player
Highlight your experience mentoring junior engineers and contributing to team knowledge. Zensar values collaboration, so share examples of how you've worked with others to elevate project quality and foster a positive team environment.