Senior Data & AI Scientist

Lloyds Banking Group; Hyderabad; Hybrid; INR 3,500,000 - 5,500,000; Full time

Job summary

Lloyds Banking Group Hyderabad hosts an AI Engineer – GradeE (Senior Level) to lead design and delivery of enterprise-scale AI/ML solutions, including LLM/GenAI features. Strong focus on reliability, security, and compliance; mentor engineers and collaborate with cross-functional teams to operationalise AI safely.

The role emphasizes architecture, MLOps practices, and governance while leveraging cloud AI stacks and secure microservices in a hybrid work setup.

Qualifications

• 7–12 years of software/ML/AI experience with production delivery.
• Strong Python and software engineering discipline; working knowledge of SQL.
• Hands-on with Docker/Kubernetes and Git-based CI/CD.

Responsibilities

• Architect and implement advanced ML and GenAI systems for enterprise use.
• Build CI/CD pipelines and manage model lifecycle with MLflow or equivalent.
• Develop RAG workflows, embeddings, and vector indexes with guardrails.
• Expose models via secure microservices with RBAC/ABAC and audit logging.
• Embed AI ethics, regulatory standards, and security controls into solutions.

Skills

Python

Software engineering

SQL

Tools

Docker

Kubernetes

Git-based CI/CD

Azure ML

Vertex AI

MLflow

Kubeflow

Airflow

Feast

Prometheus

Grafana

OpenTelemetry

KMS/Key Vault

PGVector

Weaviate

Pinecone

LangChain

LlamaIndex

Job description

End Date

Thursday 22 October 2026

We Support Flexible Working – Click here for more information on flexible working options

Flexible Working Options

Hybrid Working

Job Description Summary

AI Engineer – GradeE (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.