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.
- Good 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 Professional 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