Senior/Staff Software Engineer - ML/AI Applications
As a Technical Lead on Zoox's internal agentic platform, you will own end-to-end integration of a tool-centric agent runtime with external and internal agent clients, line of business backends, scheduled and interactive agent workloads, and cloud operations (Kubernetes, observability, secrets management). You will translate architecture and security intent into stable tool contracts, testable integration milestones, and repeatable releases, and you will be the primary engineer when issues sit at the boundary between product surfaces, platform services, and upstream systems.
This role is platform and service integration for an agentic framework that mediates tools (discovery, invocation, policy, and telemetry). Success is measured by reliable tool call paths over HTTP, correct authentication and scoping, environment parity from dev through production, and clear ownership across partner engineering, security, and infrastructure teams.
In this role, you will:
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
Qualifications:
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
Bonus Qualifications
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).