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Deployed AI Engineer

Summary

Build and deploy AI-powered features using LLMs, agents, and RAG pipelines with full-stack engineering in Python/TypeScript.

Salary: £66,000 - 106,000 per year

Requirements:
  • Strong software engineering foundations, including clean code, testing, CI/CD and a production mindset, with strong general-purpose programming skills such as Python or TypeScript and proficiency in 2+ modern languages
  • Full-stack capability across front-end, back-end and data engineering
  • Hands-on production LLM and agent experience, including prompt engineering, agent workflows, RAG, tool orchestration and MCP, with evidence of shipping AI products that users rely on
  • Evaluation-driven habits, including golden datasets, eval frameworks and guardrails
  • Client-facing delivery experience and comfort working within enterprise constraints such as security, compliance and legacy integration
  • High agency and comfort with ambiguity, with the ability to operate with minimal supervision in a client environment
  • A strong value instinct, with the ability to explain business value and identify when something is not worth building
  • Experience with vector databases, embeddings and fine-tuning is desirable
  • Cloud experience, especially AWS or Google Cloud, is desirable
  • Former founder or startup experience is desirable
  • Open-source contributions or visible AI side projects are desirable
Responsibilities:
  • Build working AI proofs on real client data during assess engagements
  • Deliver client POCs and MVPs, including RAG pipelines, agent architectures, LLM integrations and protocol-driven tooling
  • Iterate in short loops by demoing frequently, taking feedback and adapting quickly
  • Engineer for production from day one, including guardrails, security, scalability, telemetry and integration into the client environment
  • Prove trustworthiness through evaluation practices such as golden datasets, automated evaluation pipelines, accuracy and drift monitoring
  • Work with client data, including pipelines, messy edge cases and complex integrations
  • Own and evolve our internal AI platform and codify repeatable field patterns into reusable assets
  • Lead advanced technical sessions in our upskilling programme and support client engineers during transform engagements
  • Evaluate emerging AI tools, frameworks and protocols and make pragmatic adoption decisions
Technologies:
  • AI
  • AWS
  • CI/CD
  • Cloud
  • Fine-tuning
  • Support
  • LLM
  • MCP
  • Python
  • RAG
  • Security
  • TypeScript
  • CTO

More:

At Enablis, we deliver complex, high-impact technology transformation and are building a genuinely AI-native consultancy. We operate AI-first, so every recommendation comes from practitioners. This role is our technical spearhead, working in a small pod, typically with a Delivery Lead, to own end-to-end technical execution of client engagements. We work inside the clients environment, on their real data, within their security model, and we aim to move from prototype to POC to MVP in weeks. Between engagements, we extend our internal AI platform and turn what we prove in the field into accelerators, templates and playbooks. We are an equal opportunities employer and welcome applications from all suitably qualified persons regardless of race, sex, disability, religion or belief, sexual orientation or age.

last updated 33 week of 2026

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