At a Glance
- Tasks: Lead AI delivery programs, design multi-agent systems, and engage with global clients.
- Company: Zensar, a leader in digital solutions and technology services.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Other info: Dynamic environment with mentorship opportunities and cutting-edge technology.
- Why this job: Make a real impact in AI by building production-ready systems that transform businesses.
- Qualifications: Degree-level education and proven experience in deploying agent-based systems.
The predicted salary is between 70000 - 90000 £ 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
- RAG & Vector Stores: Chroma, Weaviate, Pinecone, know where RAG breaks
- 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
- 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 2–3 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 employer: Zensar Technologies
Zensar is an exceptional employer that fosters a dynamic work culture focused on innovation and collaboration, making it an ideal place for AI professionals to thrive. With a commitment to employee growth, Zensar offers opportunities to lead cutting-edge AI projects while working directly with global clients, ensuring that your contributions have a meaningful impact. Located in a vibrant tech hub, the company provides access to the latest tools and technologies, empowering you to stay ahead in the rapidly evolving field of AI.
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We think you need these skills to ace AI Lead
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