1 day ago
Bengaluru, IndiaSenior
Responsibilities
- Build and maintain GitHub Actions CI/CD pipelines for Python applications, ML models, and GenAI/LLM services.
- Implement branching, versioning, artifact promotion, and deployment automation across DEV, SIT, and PROD environments.
- Automate Databricks jobs, notebooks, workflows, model-serving deployments, Azure ML endpoint deployments, canary rollouts, and rollbacks.
- Integrate MLflow for experiment tracking, model registry, Unity Catalog promotion, and tracing.
- Implement automated quality gates, LLM evaluation harnesses, regression tests, and model validation checks.
- Configure GenAI guardrails including filtering, PII redaction, prompt-injection and jailbreak checks, and Azure AI Content Safety.
- Set up observability, monitoring, and alerting for latency, token usage, cost, tool calls, failures, data drift, model performance, and endpoint health.
- Manage secrets, service principals, and OIDC authentication between GitHub Actions, Azure, and Databricks.
- Containerize applications with Docker and deploy them to existing AKS or Azure Container Apps environments.
- Partner with data scientists and GenAI engineers to productionize notebook-based use cases reliably.
Requirements
- 6–10 years of experience in DevOps, platform, or ML engineering roles.
- Strong hands-on experience building GitHub Actions pipelines using reusable workflows, matrix builds, environments, approvals, and self-hosted runners.
- Strong Python skills plus Bash, YAML, and Git experience.
- Hands-on Databricks experience with Workflows, Unity Catalog, MLflow, Model Serving, Asset Bundles, and the Databricks CLI.
- Working knowledge of Azure ML, ADLS Gen2, Key Vault, ACR, AKS or Container Apps, Entra ID service principals, and Azure Monitor.
- Practical MLOps experience with model packaging, registries, versioning, automated retraining, drift monitoring, and performance monitoring.
- Practical LLMOps experience with production GenAI applications, including RAG and frameworks such as LangChain or LangGraph.
- Hands-on experience implementing LLM guardrails and evaluation systems.
- Experience with Docker, container-based deployment, observability tooling, application tracing, and metrics instrumentation.
- Bachelor’s degree in Computer Engineering, Computer Science, or Information Technology, or a master’s degree in Computer Science.
- Azure or Databricks certification, regulated-industry model governance experience, Langfuse or LangSmith exposure, inference cost optimization experience, and Azure DevOps pipeline familiarity are preferred.
- English proficiency at Advanced C1 level is required; Certified Kubernetes Administrator and HashiCorp Certified Terraform Associate certifications are listed.
Benefits
- Hybrid work arrangement with a flexible work shift in India.
- Regular employment with mentorship, learning opportunities, and career development.
- Opportunity to work on AI-powered transformation and enterprise technology initiatives.
- Values-driven workplace emphasizing inclusion, integrity, collaboration, and innovation.
Categories
About Genpact
Genpact is a global professional services and technology firm that runs and transforms mission-critical operations for large enterprises through consulting, managed services, and AI- and analytics-driven platforms. It serves industries such as banking, insurance, healthcare, and manufacturing/supply chain, modernizing finance, risk, customer service, and back-office processes. Headquartered in New York and listed on the NYSE (G), Genpact originated within GE before becoming an independent public company.