Senior/Staff Software Engineer - ML/AI Applications

Own and lead integration strategy and execution across hosted services, shared libraries, standardized tool protocols (e.g., JSON-RPC over HTTP), REST APIs, and diverse callers (vendor agents, consoles, automation workers).

Drive cross-functional delivery with backend API teams, partner agent owners, security, SRE/platform, and program management, ensuring formal sign-off where required.

Debug and root-cause complex failures using structured logs, distributed traces, metrics, and gateway/session-token behavior, documenting durable mitigations and runbooks.

Define and review all integration artifacts (contracts, allowlists, registry config, environment matrices, and interface assumptions) that upstream and downstream teams implement against.

Contribute to release gating by ensuring container image promotion, configuration/secrets posture, smoke path execution for high-traffic flows, and disciplined branching/tagging for production intent

BS or MS in Computer Science or a related field with 7+ years of software engineering experience, strong in integration, platform, or backend roles.

Strong Python (production services, async I/O, automated testing) and comfort in a large monorepo with CI-driven delivery.

Deep experience with HTTP integration (REST/JSON-RPC, TLS, debugging under load) and shipping services on Kubernetes (deployments, health checks, troubleshooting).

Auth integration experience: bearer tokens, JWT validation, OAuth2/OIDC or enterprise SSO concepts, and least-privilege scoping

Exposure to Model Context Protocol (MCP) or similar agent tool-calling and orchestration models used in industry or internal platforms.

Observability-led integration habits: metrics, traces, structured logging, and basic SLO or dashboard thinking for integration health.

Background in security-sensitive integrations (data minimization, external partner access, review cycles with security or compliance).