Software Engineer, Connectors & MCP

Responsibilities

• Design and deliver secure, scalable AI integration platforms that connect enterprise systems and power mission‑critical automation.
• Contribute to the design and evolution of our AI integration client ecosystem, defining how AI applications securely connect to external tools, data sources, and enterprise systems.
• Own backend service design for high‑throughput, low‑latency APIs that enable reliable agent workflows and complex cross‑system orchestration.
• Set technical direction for identity, auth, and trust boundaries across integrations (OAuth, API key, service‑to‑service), balancing developer velocity with security and compliance.
• Partner with product and cross‑functional engineering leaders to shape roadmap, define technical strategy, and translate ambiguous business goals into durable platform capabilities.
• Lead production excellence through a metrics‑first reliability strategy, defining and enforcing SLOs/SLAs, maturing observability, and driving resilience, incident readiness, and performance optimization at scale.
• Raise the engineering bar through architecture reviews, pragmatic design standards, rigorous testing strategy, and mentorship of senior and mid‑level engineers.

• 5+ years of software engineering experience building and operating production backend systems using Typescript, Deno, Node.js, or Bun; scope and leveling can flex across Senior to Staff based on architectural impact and leadership.
• Strong experience designing and shipping API‑driven platform services and distributed systems, including microservices, event‑driven patterns, and secure service‑to‑service communication.
• Practical expertise building AI integration layers (e.g., MCP clients/servers, tool orchestration, external API connectors, auth mediation), not just prompt or model experimentation.
• Deep hands‑on knowledge of authentication and security patterns for third‑party integrations (OAuth2/OIDC, API keys, token lifecycle, secret management, least‑privilege access).
• Proven cloud‑native experience on AWS, GCP, or Azure, including containerized workloads (Docker/Kubernetes), CI/CD, and production operations.
• Strong experience with observability and reliability engineering, including defining/operating service metrics, SLOs/SLAs, alerting, incident response, and performance tuning.
• Solid backend fundamentals in modern server frameworks and data systems (e.g., Type Script/Node or Python ecosystems, PostgreSQL), with ability to choose the right tool for the system; experience with Python is a plus but not required.
• Demonstrated ability to lead through ambiguity: partner cross‑functionally, mentor engineers, drive technical decisions, and own delivery from design through production.
• You embody our core values of Connect, Challenge, and Own. You build strong partnerships across teams, challenge conventional thinking to drive innovation, and take ownership of your work with a focus on delivering meaningful impact and excellence.