Functional Focus: Data Engineering, Real-Time Streaming, and HPC Job Orchestration
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Scientific Data Architecture: Design crash-safe, binary data formats capable of handling high-speed incremental writes from compute jobs and concurrent reads for query-time calculations.
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Operational Data Modeling: Design and maintain a relational database schema via an async ORM, backend-agnostic across database engines.
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HPC Workload Management: Manage the lifecycle of batch and interactivecompute jobs, handling subprocess monitoring, status polling, and cluster filesystem coherency.
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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.
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AI Service Integration: Integrate and orchestrate calls to an AI/analytics service from the backend, coordinating with application state.
Requirements
Mandatory:
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Python 3, async/await
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FastAPI (or similar async Python web framework)
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Relational DB modeling, async ORM (e.g. Tortoise, SQLAlchemy), SQL
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Server-Sent Events or WebSockets, backpressure handling
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Role-based access control (RBAC), token-based auth (JWT/OAuth)
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Subprocess management, batch job lifecycle/status polling
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Binary/streaming file format design, crash-safe writes
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REST/SDK integration with an external AI/LLM service
Optional:
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Go or another async-capable backend language
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GraphQL
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PostgreSQL administration, Alembic/migrations tooling
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Message queues/brokers (Redis, RabbitMQ, Kafka)
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Air-gapped/offline deployment experience
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HPC schedulers (SLURM, PBS), Linux cluster filesystems
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NumPy/columnar formats (Parquet, HDF5)
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Tool-calling / function-calling orchestration patterns
Benefits
We offer great career growth, ESOPs, Gratuity, PF and Health Insurance.
