Job Summary

Reports to

Programme Tech Lead

Capabilities covered

Standardized Data Platform Architecture; Standardized AI/ML Framework; MLOps Maturity; AI/ML Infrastructure Enhancements

Location

Prudential VCC Bangalore (preferred)

Role summary

Lead the design and conformance of the cloud-agnostic MLOps framework and AI/ML infrastructure (vector search, embeddings) across Azure Databricks and GCP Vertex AI.

Key Responsibilities
Maintain the standardised AI/ML framework design covering experimentation, code versioning, CI/CD, feature management, deployment, inference and monitoring.
Validate the AI/ML infrastructure baseline at mobilisation, close spillover and support adoption; do not restart completed work.
Guide self-service Terraform templates for vector search and embedding infrastructure in Databricks and Vertex AI.
Oversee MLOps framework rollout to remaining LBUs and ensure co-existence with the AI Platform (Scope 3) capabilities.




Review designs from ML Integration Engineers for security, scalability and Group standards alignment.

Skill Requirements

Must-have skills and experience
7–10 years in ML/AI architecture with production MLOps experience.
Hands-on MLflow, Databricks ML, and/or Vertex AI pipelines and model registries.
Experience designing cloud-agnostic ML platforms and CI/CD for ML.
Valuable understanding of vector search, embeddings and GPU/compute optimisation.

Good to have
Exposure to GenAIOps, LLM gateways and RAG patterns.
Insurance or BFSI ML use cases (fraud, churn, claims).

Certifications (within 90 days of assignment)
Databricks ML Qualified / Generative AI Engineer
GCP Skilled Machine Learning Engineer
HashiCorp Terraform Associate

Must Have Skill

AI/ML Tools - Others

Good to Have Skill

Other Requirements

📌 Senior Technical Specialist Bengaluru
🏢 HCLTech
📍 Bengaluru