- Distributed systems, APIs and microservices
- Event-driven architecture
- Strong AWS experience across compute, storage, networking and IAM
- Ability to turn unclear business goals into technical architecture
- Experience supporting ML inference pipelines, including data normalization, feature pipelines, feature stores or model-serving integrations
- Demonstrated use of GitHub Copilot, LLM-powered development workflows or agentic coding tools
- Comfortable working at startup speed with evolving requirements
Strongly preferred:
- Edge computing or CDN execution experience
- Edge workers, CDN functions, or equivalent
- JWT/JWS, OAuth 2.0, PKI, token validation or identity/security platforms
- Python and Databricks
- ML model-registry integration
- Distributed tracing, structured logging and observability
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