Senior Data & AI Scientist
Lloyds Banking Group Hyderabad, Telangana, India
Financial Services · 10,001+ employees
About the role
Lead the design and delivery of enterprise-scale AI/ML solutions, including LLM and GenAI features, with a focus on reliability and security. Drive technical standards, mentor junior engineers, and collaborate with cross-functional teams to operationalize AI safely.
What they look for
Requirements
Requires 7–12 years of experience in software, ML, or AI with proven technical leadership and production delivery. Essential skills include Python, cloud AI stacks, MLOps practices, and a deep understanding of LLM fundamentals.
Benefits
Full description
End Date
Monday 07 September 2026
We Support Flexible Working – Click here for more information on flexible working options
Flexible Working Options
Hybrid Working
Job 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.
