AI Practice Lead

ZensarLondon, EnglandOn-siteFull-timeSenior, 5–8 yearsListed 7 hours ago

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About this role

Engineering Foundation

Non-negotiable. This is what we screen on first, and there is no AI in it.

- Data modelling across SQL and NoSQL, and a clear view of where each one breaks
- Event-driven architecture in production with Kafka, RabbitMQ or equivalent. Ordering, replay, idempotency, dead-letter handling
- Distributed systems failure modes: partial failure, retries, backpressure, timeouts, circuit breakers
- Caching strategy and invalidation, at a scale where getting it wrong hurt
- Observability. You have instrumented a system, not just read someone else's dashboard
- At least one cloud deeply. Not three superficially
- API and integration patterns against real enterprise surfaces such as ERPs, CRMs and data platforms
- CI/CD, containers, release engineering
- You have owned something in production. On-call, incidents, the whole thing

Agent systems are distributed systems with a non-deterministic component in the middle. If the fundamentals are not there, the AI layer does not survive contact with production.

What We Are Not Looking For

- Someone who lists LLMs on a resume but has only called the API in a notebook
- People who explain everything in terms of frameworks they have never deployed
- Consultants who can only narrate what others have built
- Engineers who cannot hold a client conversation, and client-facing people who cannot build

How We Will Evaluate You

Stage 0, System design with no AI. A distributed systems problem with no LLM in it. Event flow, data model, failure handling, scale. Twenty-five minutes.

Stage 1, Technical screen. Walk us through a system you built. Bring an artifact: an eval set, a trace from a run that failed, a postmortem, a cost-per-task number. Something real, not slides.

Stage 2, Architecture discussion. A business problem, live. Design the solution and defend the trade-offs, including the decision not to use agents.

Stage 3, Client simulation. Present your approach to a non-technical executive audience, then advise them on how to build the capability internally.