Functional Focus: Data Engineering, Real-Time Streaming, and HPC Job Orchestration
Scientific Data Architecture: Design crash-secure, binary data formats capable of handling high-speed incremental writes from compute jobs and concurrent reads for query-time calculations.
Operational Data Modeling: Design and maintain a relational database schema via an async ORM, backend-agnostic across database engines.
HPC Workload Management: Manage the lifecycle of batch and interactivecompute jobs, handling subprocess monitoring, status polling, and cluster filesystem coherency.
Real-Time API & Streaming: Build async backend services and long-lived, server-pushed event channels with backpressure handling, and enforce role-based access control on all APIs.
AI Service Integration: Integrate and orchestrate calls to an AI/analytics service from the backend, coordinating with application state.

Requirements

Mandatory
Python 3, async/await
FastAPI (or similar async Python web framework)




Relational DB modeling, async ORM (e.g. Tortoise, SQLAlchemy), SQL
Server-Sent Events or WebSockets, backpressure handling
Role-based access control (RBAC), token-based auth (JWT/OAuth)
Subprocess management, batch job lifecycle/status polling
Binary/streaming file format design, crash-safe writes
REST/SDK integration with an external AI/LLM service

Optional
Go or another async-capable backend language
GraphQL
PostgreSQL administration, Alembic/migrations tooling
Message queues/brokers (Redis, RabbitMQ, Kafka)
Air-gapped/offline deployment experience
HPC schedulers (SLURM, PBS), Linux cluster filesystems
NumPy/columnar formats (Parquet, HDF5)
Tool-calling / function-calling orchestration patterns

Advantages

We offer great growth opportunities, ESOPs, Gratuity, PF and Health Insurance.

📌 Systems & Data Infrastructure Engineer Bengaluru (India)
🏢 Astrome Technologies
📍 India