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

enterprise environments.

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
• DevOps primarily).
• 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
• adoption.
• 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
• Kong API Gateway, Kong Mesh, Flux CD.
• RESTful API development (FastAPI preferred), microservices, Terraform with
• GitOps workflows.
• IaC & Terraform experience with GitOps workflows.
• Prompt redteaming & evaluation tools (like Promptfoo & Arize).
• Experience with SQL (MySQL, PostgreSQL) and NoSQL (MongoDB, Cassandra)
• databases 
• Exposure to RAG patterns and vector search technologies.
• Behavioural Competencies
• 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.