At CEEW, we are deliberate about what we stand for as an employer. So, if the below description strikes a chord, we would love to hear from you!
At CEEW, we build careers in public policy
- We offer strong visionary leadership – with emphasis on research and impact at scale
- We actively promote leadership by initiative
- We celebrate talent and ambition
- You will be surrounded by smart people who will challenge you and help you grow
- You will learn faster than your peers in other organisations
- Curiosity and irreverence, as well as responsibility, come together at CEEW
- You will get above-market remuneration
- We provide a safe space for all
- At CEEW, your life is your example for others
Designation offered
DevOps Engineer: AI & Geospatial Platforms
Team/ Focus area
Technology & AI
Location
New Delhi
Duration
Full Time
Job Duties and Accountabilities
Primary responsibilities
Infrastructure & Cloud Operations
- Design, provision, and maintain cloud infrastructure (GCP/AWS) for AI, geospatial, and data-intensive workloads across the Tech & AI portfolio
- Manage compute environments for ML training, inference, and large-scale satellite data processing (Dask/Coiled, Vertex AI, GPU/TPU workloads)
- Optimise cloud spend through right-sizing, autoscaling, spot/preemptible usage, and storage lifecycle policies
- Maintain data pipeline infrastructure for geospatial ETL (NetCDF/Zarr/GeoTIFF), vector/graph databases, and RAG/agentic systems
CI/CD & Release Engineering
- Build and own CI/CD pipelines (GitHub Actions / GitLab CI) for backend services, ML models, dashboards, and data pipelines
- Establish containerisation standards using Docker and orchestration via Kubernetes / Cloud Run
Observability, Reliability & Security
- Set up monitoring, logging, and alerting stacks (Cloud Logging, Sentry) across applications, APIs, and ML services
- Implement security controls: IAM, secrets management (Vault / Secret Manager), vulnerability scanning, network policies
Data Platform Support
- Support API infrastructure for platforms like CRAVIS — gateway, rate limiting, authentication, versioning
- Partner with AI, geospatial, and product teams to unblock environment, deployment, and scaling issues
Selection Criteria
Qualification
Educational
- B.E./B.Tech in Computer Science, IT, or equivalent from a reputed engineering institute. Relevant certifications (GCP Professional DevOps Engineer, AWS DevOps, CKA) preferred.
Must Have (Hands-on Experience)
- 4+ years operating production cloud infrastructure on GCP or AWS
- Strong hands-on with Docker, Kubernetes
- Solid scripting in Python and Bash; comfort with Linux internals and networking
- Experience building and maintaining CI/CD pipelines for both application and data/ML workloads, working knowledge of observability tooling
- Experience managing PostgreSQL/PostGIS or similar databases in production
Preferred
- Experience supporting ML/AI workloads, GPU provisioning, model serving (Vertex AI Endpoints, AWS Boto), MLOps tools (MLflow, Weights & Biases)
- Familiarity with geospatial data stacks (PostGIS, GeoServer, TiTiler, COG/Zarr workflows)
- Exposure to LLM/agentic infrastructure: vector databases, embedding pipelines, observability for agents
- Experience with government cloud or DPI-aligned deployments
- Prior work in climate tech, public-data systems, or mission-driven organisations
Compensation
Competitive compensation – commensurate with the experience and matching the best of the standards adopted by the industry or other similar organisations for similar roles.
Application Process
CEEW is an equal opportunity employer, and the selection process does not discriminate on the basis of age, gender, caste, ethnicity, religion, or sexuality. Female candidates are encouraged to apply. Applications will be reviewed on a rolling basis. Interested applicants are advised to apply at the earliest possible time. Only shortlisted candidates will be notified. We appreciate your interest.
