About GalaxEye :
We build the world's first SyncFused OptoSAR satellites and the software backbone that runs them from TT&C and mission ops to high-throughput geospatial AI pipelines. This role is modeled to match top industry platform leads at companies building operational EO + analytics stacks.
Why this role matters
You'll build the platform that connects satellites ground AI: mission control, telemetry & command, high-volume imagery ingestion, COG/GeoParquet storage, GPU-backed model training/inference and customer data delivery reliable at scale and deployable in cloud and on-prem.
What success looks like (first 612 months)
- Deliver a vetted reference architecture for Mission & Data Platforms (hybrid cloud + hardened on-prem).
- Ship a CI/CD pipeline, container strategy, and a working devstagingprod flow for mission services.
- Provision a baseline on-prem hardware spec (compute, GPU, storage, networking) and a costed procurement plan.
- Deploy a production data ingress pipeline that accepts raw imagery (satellite frames, SAR bursts), produces COGs/GeoParquet/tiles, and feeds model training/inference.
- Hire/mentors first 36 platform engineers and codify SRE/hygiene standards (SLOs, runbooks, blameless postmortems).
Responsibilities (hands-on leadership)
- Architecture & Tech Direction
- Define end-to-end platform architecture for Mission Management (TT&C, scheduler, health/telemetry) and Data Management (ingest, catalog, processing, serving).
- Ensure platform interoperability with AI/foundation models provide model hosting, feature stores, model-versioning, and low-latency inference endpoints for computer-vision & geospatial workloads.
- Tech Stack & Implementation
- Select and own core stack (see Preferred tech stack below).
- Design hybrid deployment patterns: cloud native (GCP/AWS) and hardened on-prem (bare-metal/K8s/OpenStack/VMware).
- DevOps / SRE / Hygiene
- Build CI/CD, IaC, observability, security, secrets management, and blue/green/rolling deployments.
- Define SLOs/SLIs, runbooks, incident response and capacity planning.
- Data & AI Integration
- Work with Data Science/ML engineers to design training pipelines (data versioning, dataset formats such as COG/GeoParquet/Iceberg), GPU scheduling, and model deployment (Triton/KFServing/MLflow).
- Ground & Mission Ops
- Integrate with ground station stacks, scheduling systems, and mission planners. Implement telemetry pipelines (CCSDS-like framing, TM/TC handlers) and mission workflows.
- Hardware Sizing & Procurement
- Size compute/GPU/storage/network (IOPS, throughput, retention) and produce costed specs for procurement. Recommend RAID/erasure/cluster configs (Ceph/Lustre/NAS).
- Team Building
- Recruit, grow, and lead a cross-functional team (Platform Engineers, DevOps, SRE, Systems Administrators). Set OKRs and technical KPIs.
Must-have (non-negotiable)
- 8+ years building production platforms / infrastructure / DevOps (or equivalent).
- Deep, hands-on experience with Kubernetes + containers, container networking, and cluster ops at scale.
- Proven track record of designing hybrid cloud + on-prem architectures and running secure, high-availability services.
- Strong systems programming / backend experience (Python and/or Go).
- Experience sizing and managing GPU clusters and high-throughput storage for large raster datasets.
- Solid understanding of geospatial data formats and pipelines (COG, GeoTIFF, GeoParquet, PostGIS) and large raster handling.
- Experience with CI/CD, IaC (Terraform/Ansible), message streaming (Kafka), and orchestration (Argo/Kubernetes).
- Excellent product & people skills you can translate mission requirements into testable architecture and recruit/mentor engineers.
Nice-to-have (differentiators)
- Prior work on satellite ground systems / TT&C / telemetry and mission ops.
- Experience with SAR/image processing, GDAL/Rasterio, and raster reprojection/orthorectification.
- Familiarity with ML infra: PyTorch/TensorFlow, NVIDIA CUDA stack, Triton inference server, MLflow, or KServe.
- Knowledge of spatial servers and tiling: GeoServer, pg_tileserv, Tile38, MapProxy, or similar.
- Experience with object storage (S3/MinIO), Ceph, and high-performance filesystems (Lustre).
- Security & compliance experience for govt/defence environments.
Preferred tech stack
Languages & frameworks: Python, Go, (Node.js/Java optional)
Orchestration & CI/CD: Kubernetes (EKS/GKE/AKS + on-prem k8s), Docker, ArgoCD / Flux, GitHub Actions / GitLab CI, Jenkins (legacy support)
Infrastructure as Code: Terraform, Ansible, Packer
Messaging & streaming: Kafka (Confluent), RabbitMQ (where applicable)
Databases & catalogs: PostgreSQL + PostGIS, ClickHouse (analytics), Redis (caching), Iceberg / Delta / Parquet for analytics
Object & block storage: S3 / MinIO, Ceph, NFS, Lustre for HPC storage
Geospatial tooling: GDAL, Rasterio, COGs, GeoParquet, GeoServer, pg_tileserv, PostGIS, TileServer GL, Mapbox/Leaflet for frontends
Big data / distributed compute: Spark, Dask, Ray for parallel processing; Airflow / Prefect for orchestration
ML / inference: PyTorch/TensorFlow, NVIDIA CUDA/CUDA-aware schedulers, Triton Inference Server, MLflow / KServe
Observability & Security: Prometheus, Grafana, ELK (ELK/Opensearch), Jaeger, Vault, Falco, OPA/Gatekeeper, SSO (OIDC)
Ground & mission ops: Familiarity with CCSDS framing, COSMOS-style consoles, and telemetry ingestion libraries; ground station integration patterns.
Hardware & networking: 10/40/100GbE NICs, GPU servers (NVIDIA A100/V100 or similar), SAN/NAS design, UPS & rack-level considerations.
What We're Looking For
We're seeking a builder and systems thinker someone who thrives at the intersection of infrastructure and intelligence. You should be equally excited about architecting resilient DevOps systems and designing AI-ready platforms capable of handling complex geospatial and multi-sensor data flows.
If you want to help build the foundational software layer that enables satellites and AI to work together this is the role for you.
Why GalaxEye
- Be part of India's only multi-sensor satellite startup, building the world's first hybrid imaging constellation.
- Collaborate with top-tier engineers and scientists from IIT Madras and global space-tech communities.
- Build real deep-tech infrastructure that powers national security, global resilience, and data intelligence.
