AI Engineer

**End Date** Thursday 30 July 2026 [**We Support Flexible Working – Click here for more information on flexible working options**](http://www.lloydsbankinggroup.com/careers/culture-and-inclusion/agile-working.html) **Flexible Working Options** Hybrid Working **Job Description Summary** AI Engineer – Grade D Location: Hyderabad – Lloyds Technology Centre Function: Lending & Working Capital Platform Experience: 4–6 years (software/ML/AI); proven production delivery, hands on GenAI and Agentic AI experience Location: Hyd Mode: Hybrid YOE: 4-6 **Job Description** **Role Purpose** Lead the design and delivery of enterprise-scale AI/ML solutions—including LLM/GenAI features—with 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. **Key Responsibilities** * **AI Solution Design & Delivery:** Architect and implement advanced ML and GenAI systems; optimise for performance, cost, and scalability. * **Model Operationalisation (MLOps):** Build CI/CD pipelines, implement automated testing, and manage model lifecycle with MLflow or equivalent. * **LLMOps & GenAI:** Develop RAG workflows, embeddings, and vector indexes; enforce prompt safety, observability (latency, token usage, cost), and guardrails. * **APIs & Integration:** Expose models via secure microservices (FastAPI or similar); ensure RBAC/ABAC and audit logging. * **Governance & Compliance:** Embed AI ethics, regulatory standards, and security controls into all solutions. **Essential Skills** * Strong Python and software engineering discipline; working knowledge of SQL. * Hands-on with Docker/Kubernetes and Git-based CI/CD (GitHub/Azure DevOps). * Experience with cloud AI stacks (GCP Vertex AI), artefact registries, and secrets management. * Deep understanding of LLM fundamentals (prompting, embeddings, RAG, guardrails). * Familiarity with MLflow/Kubeflow, Airflow/Composer, and feature stores (e.g., Feast). **Desirable Skills** * Vector DBs (PGVector/Weaviate/Pinecone), LangChain/LlamaIndex. * Observability tools (Prometheus/Grafana/OpenTelemetry) and model evaluation frameworks (Evidently, Ragas/TruLens). * Secure engineering practices: tokenisation/masking, KMS/Key Vault, policy-as-code.