The Role
Lead design and delivery of enterprise-scale AI/ML and GenAI systems, oversee MLOps and LLMOps (RAG, embeddings, vector indexes), build CI/CD/model lifecycle pipelines, expose secure model APIs, enforce governance, mentor engineers, and optimize for performance, cost, reliability, and compliance.
Summary Generated by Built In
End Date
Wednesday 24 June 2026We Support Flexible Working – Click here for more information on flexible working options
Flexible Working Options
Hybrid WorkingJob Description Summary
AI Engineer – Grade E (Senior Level)Location: Hyderabad – Lloyds Technology Centre
Function: Chief Data & Analytics Office (AI CoE)
Experience: 7–12 years (software/ML/AI); proven production delivery and technical leadership
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.
Job Description
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 (Azure ML or 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.
Skills Required
- 7-12 years experience in software/ML/AI with 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) and automated testing
- Experience with cloud AI platforms (Azure ML or GCP Vertex AI) and artifact registries/secrets management
- Experience with MLflow or equivalent model lifecycle tools (Kubeflow) and MLOps practices
- Familiarity with Airflow/Composer and feature stores (e.g., Feast)
- Deep understanding of LLM fundamentals (prompting, embeddings, RAG, guardrails) and LLMOps
- Ability to expose models via secure microservices (e.g., FastAPI) with RBAC/ABAC and audit logging
- Embed AI governance, ethics, regulatory standards, and security controls into solutions
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The Company
What We Do
Lloyds Technology Centre is the Global Capability Centre of Lloyds Banking Group, based in Hyderabad, India. It functions as a tech and data company providing engineering expertise in cloud computing, data analytics, and cybersecurity. The centre supports the digital transformation of Lloyds Banking Group, a leading UK financial services provider, and operates primarily in the IT services and consulting sector.
