Job Description

Job Title: Python API Developer

Location: Remote

Duration: / Term: C2C

Experience Desired: 9+ Years

Job Description:

• Build serving stores and REST APIs that deliver governed data at the latency and scale production use cases demand.
• Own API contract design, versioning strategy, and breaking-change policy for data-serving APIs.
• Build and operate Change Data Feed (CDF) based sync pipelines to low-latency serving stores.
• Implement caching patterns - invalidation strategies, TTL management, and hot-path serving - for sub-millisecond response times.
• Design and build serving infrastructure for AI use cases including vector databases, graph databases, and agent-facing data patterns.
• Set up CI/CD pipelines from scratch with automated tests covering sync correctness, API contract validation, and latency benchmarks.
• Partner with domain teams to onboard use cases, mentor engineers, and contribute to reusable blueprints and reference implementations.

What You'll Bring

• 7+ years of software engineering experience focused on data infrastructure and backend systems.
• Production Python with API development; owns API versioning, contracts, and governance.
• Experience with CDF-based incremental sync pipelines.
• Production experience distributed data processing and transformation.
• Production caching and key-value serving: Redis or comparable; cache invalidation, TTL strategies, and high-throughput hot-path serving.
• Streaming frameworks (Kafka or comparable) for real-time data paths including CDC and incremental batch patterns.
• Familiarity with vector databases and graph databases for AI-powered serving use cases.
• Strong SQL, data modeling, and CI/CD skills; has set up CI/CD pipelines from scratch with automated testing.

Must Have Skills

• API development, Python
• Low latency data serving. Redis / Caching frameworks
• Kafka / Streaming frameworks
• CDF-based incremental sync pipelines

Nice-to-Have

• Prior experience in large-enterprise data serving or platform engineering environments.
• Experience with Knowledge graphs
• Building data infrastructure for AI use cases: RAG pipelines, agent tooling, or feature serving.

Key Skills:

Python, AI/ML, RestAPI, FastAPI, LLM, RAG.

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