AI Engineer

Overview

Lead the design and delivery of enterprise-scale AI/ML solutions, including LLM/GenAI features, with a strong focus on reliability, security and compliance. Drive technical standards, mentor junior engineers and collaborate with cross-functional teams to operationalise AI safely and efficiently.

What you'll do

• Architect and implement advanced ML and GenAI systems, optimising for performance, cost and scalability.
• Build CI/CD pipelines, implement automated testing and manage the model lifecycle with MLflow or equivalent.
• Develop RAG workflows, embeddings and vector indexes; enforce prompt safety, observability (latency, token usage, cost) and guardrails.
• Expose models via secure microservices (FastAPI or similar) and ensure RBAC/ABAC and audit logging.
• Embed AI ethics, regulatory standards and security controls into all solutions.

What you'll need

• 4 to 6 years of experience in software, ML or AI.
• Proven production delivery and technical leadership.
• Strong Python and software engineering discipline.
• Working knowledge of SQL.
• Hands-on experience with Docker and Kubernetes.
• Experience with Git-based CI/CD (GitHub or Azure DevOps).
• Experience with cloud AI stacks (Azure ML or GCP Vertex AI), artefact registries and secrets management.
• Deep understanding of LLM fundamentals (prompting, embeddings, RAG, guardrails).
• Familiarity with MLflow or Kubeflow, Airflow or Composer, and feature stores (e.g., Feast).

Nice to have

• Vector DBs (PGVector, Weaviate, Pinecone), LangChain or LlamaIndex.
• Observability tools (Prometheus, Grafana, OpenTelemetry) and model evaluation frameworks (Evidently, Ragas, TruLens).
• Secure engineering practices: tokenisation/masking, KMS/Key Vault, policy-as-code.

Details

• Location: Hyderabad, Lloyds Technology Centre.
• Function: Chief Data & Analytics Office (AI CoE).
• Hybrid working.
• End date: Friday 30 October 2026.