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Metro location but specialized HPC/async data stack reduces qualified applicant density.
Specialized HPC and streaming data infrastructure skills reduce cross-industry transferability.
Many mandatory, specific technical requirements imply high shortlisting strictness.
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Design and implement crash-safe binary data formats for high-speed incremental writes and concurrent real-time querying.
Manage HPC workload lifecycle including batch and interactive compute jobs with subprocess monitoring and cluster filesystem coherency.
Build async backend services with real-time streaming APIs (Server-Sent Events/WebSockets) enforcing role-based access control and integrate AI/analytics service calls.
Proficient in Python 3 with async/await and FastAPI or similar async Python web framework.
Experience with relational database modeling, async ORM (e.g. Tortoise, SQLAlchemy), and SQL.
Skilled in streaming technologies (Server-Sent Events or WebSockets) with backpressure handling and implementing RBAC and token-based authentication (JWT/OAuth).
Experience managing subprocesses and batch job lifecycle/status polling; designing crash-safe binary/streaming file formats. Work Experience Required: Not explicitly mentioned in the JD.
Experience working in scientific or HPC data architecture environments involving complex batch and interactive compute job orchestration.
Comfortable operating in backend service environments that require real-time streaming, async API development, and secure access control.
Familiarity with integrating external AI/LLM services and managing sophisticated data workflows involving concurrency and filesystem coherency.