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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