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Python Developer

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Summary

6-month contract (inside IR35, hybrid in London, £400–500/day) building backend services, APIs, and GenAI/agentic components — prompt orchestration, LLM integration, RAG, CI/CD — on an enterprise generative-AI platform for a large global insurer, using Python, FastAPI, and AWS.

Contract Role, Hyrbrid/London, Inside of IR35, 400-500 PD 6 months

We are seeking a senior and experienced GenAI & Agentic Developer to build core

services, features and capabilities on an enterprise-grade Generative AI Platform for

a large global insurer. This role blends strong Python engineering with DevOps

enablement and hands-on integration of LLM technologies into secure, scalable

The ideal candidate will bring practical GenAI & Agentic development experience,

strong automation skills, and the curiosity to solve emerging engineering challenges

in this rapidly evolving space.

Key Responsibilities

  • Build and maintain backend services and APIs enabling secure access to LLM capabilities.
  • Develop and optimise Python-based GenAI & Agentic components including prompt orchestration, output validation, and evaluation tooling.
  • Integrate LLMs with enterprise systems, observability, and security frameworks.
  • Design and maintain CI/CD pipelines aligned to engineering standards (Azure
  • Collaborate closely with platform leads, architects, and SRE teams to ensure reliable operationalisation of GenAI services.
  • Support benchmarking, evaluation, and experiment tracking for LLM performance and cost.
  • Contribute to RAG implementations and data access patterns supporting enterprise use cases.
  • Help shape API standards, reusable patterns, and documentation for platform
  • Troubleshoot and optimise performance across distributed systems and cloud services.

Mandatory Skills & Experience

  • Strong Python backend engineering in production systems (inc FastAPI).
  • AWS services: EC2, EKS, S3, SQS, Kenesis/Firehose, Bedrock and AgentCore.
  • Working knowledge of GenAI technologies and Large Language Models.
  • Experience evaluating LLM performance and prompt handling complexities.
  • Solid DevOps mindset with CI/CD expertise and observability best practices.
  • Comfortable working in regulated enterprise environments with strict security controls.
  • Experience integrating AI services into real-world apps or workflows.
  • Knowledge of authentication, secret management, network boundaries, and model access governance

Preferred Skills

  • RESTful API development (FastAPI preferred), microservices, Terraform with GitOps workflows.
  • IaC & Terraform experience with GitOps workflows.
  • Experience with SQL (MySQL, PostgreSQL) and NoSQL (MongoDB, Cassandra) databases
  • Exposure to RAG patterns and vector search technologies.
  • Proactive self-starter who identifies gaps and drives solutions without waiting for tickets.
  • Comfortable working in ambiguous emerging domains where best practice is evolving.
  • Collaborative communicator able to influence and gain trust across engineering, data, and product teams.
  • Curiosity to explore and adopt new GenAI techniques in a structured, secure way.
  • Bias toward automating everything to reduce toil and accelerate delivery.

What Success Looks Like

  • Efficient, secure, and reusable GenAI components delivered into production.
  • Improved engineering velocity through automation and DevOps best practices.
  • Stable services, with observability and evaluation built in from day one.
  • Platform teams and application teams love using what you build.
  • Clear documentation and fast onboarding for future use cases.

Skills

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