AI and DATA - MlOps/AI Engineering - Senior (4+)
ey | 127 days ago | Bengaluru

Key responsibilities

  • Design, build, and operate production grade AI services/APIs, owning reliability, scalability, and performance SLOs.
  • Implement MLOps best practices (experiment tracking, model packaging, CI/CD for models, automated testing, feature and model registries, telemetry) to reduce time to production.
  • Drive DevOps automation (infrastructure as code, containerization, orchestration) and secure delivery with least privilege, secrets management, and policy-as-code.
  • Lead deployment of AI components to AWS/Azure (containers, serverless, managed ML platforms) with strong observability and rollback plans.
  • Collaborate cross functionally to translate product and analytics requirements into well designed APIs, contracts, and SLAs.

 

Must have skills

  • MLOps (e.g., MLflow/Kubeflow/SageMaker/Azure ML), CI/CD for ML, model registry, monitoring
  • DevOps (Docker, Kubernetes, IaC—Terraform/Bicep, GitHub/GitLab Actions/Azure DevOps)
  • Python (production code quality, testing, packaging)
  • Deployment to AWS/Azure (EKS/AKS, ECS/Fargate, Lambda/Functions, API Gateway/App Gateway)
  • API development (FastAPI/Flask, OpenAPI/Swagger, authN/Z, rate limiting, versioning)

 

Good to have

  • GenAI/Agentic concepts, vector databases, prompt engineering fundamentals

 

Qualifications & experience

  • B.Tech/M.Tech/MS in CS/EE or equivalent.
  • 4+ years in AI Engineering
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