Staff Software Engineer, AI Tools

Pinterest•San Francisco, CA

1d•Remote

About The Position

The IT Collaboration and Productivity Engineering team builds and runs the collaboration and productivity platforms that power how Pinployees communicate, share information, and get work done. We own core SaaS platforms such as Google Workspace, O365, Gemini, Jira, Confluence, Slack, and other collaboration, productivity, and AI tools, and partner closely with Security, People, Legal, and Engineering to design secure, reliable, and intuitive experiences. As a Staff Software Engineer, AI tools, you will be the technical lead for how third‑party AI tools — such as Claude, Glean, Granola, etc. — connect to Pinterest, and a key owner of the custom MCP servers and integrations that expose our internal tools (Slack, Google Workspace, Atlassian, and others) to those tools. You will shape the long‑term architecture for secure AI connectivity, drive major cross‑functional initiatives, and mentor others in building robust, automation‑driven solutions at the frontier of enterprise AI adoption.

Requirements

7+ years of professional software engineering experience, including significant hands‑on ownership of building and operating production services or platform integrations in a medium‑to‑large environment.
Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related field, or equivalent practical experience.
Strong programming skills in one or more backend languages (e.g., Python, Go, Java, TypeScript/Node) and solid software design and architecture ability — designing APIs and backend services, choosing appropriate abstractions, and building for maintainability, testability, and extension.
Deep, hands‑on expertise in authentication and authorization — OAuth 2.0/2.1, OIDC, SAML, token exchange, PKCE — and the failure modes that come with them.
Strong systems design and troubleshooting skills, including debugging issues that span clients, network, identity, edge/ingress (Envoy or similar), and backend services.
Experience building and integrating with APIs and services — REST/RPC, webhooks, and SDKs — including connectors against SaaS/tool APIs (Slack, Google Workspace, Atlassian, or comparable).
Grounding in engineering quality practices: automated testing, code review, CI/CD, observability, and safe production rollout.
Familiarity with the Model Context Protocol (MCP) and the emerging AI‑connector/gateway ecosystem, and with security, privacy, and compliance controls relevant to external integrations (SSO/SCIM, DLP, access reviews).
Proven use of AI tools to speed up engineering work (e.g., generating code, tests, runbooks, or summaries), with a clear approach to validating outputs, reducing bias, and protecting reliability and security.
Track record of operating at a staff‑level scope: leading large, complex initiatives, shaping cross‑team roadmaps, and owning impactful outcomes.
Ability to lead and mentor other engineers, give clear technical direction, and partner effectively with managers, product owners, and stakeholders.
Comfort working across diverse teams and locations, consistently modeling Pinterest’s values: putting Pinners and Pinployees first, aiming for high quality, acting as one team, and approaching challenges with a “win or learn” mindset.

Nice To Haves

Kubernetes/EKS and infrastructure‑as‑code (Terraform) a plus.

Responsibilities

Own third‑party AI tools connectivity end‑to‑end – act as the primary technical authority for how external AI tools authenticate to Pinterest, where their traffic flows, what internal data they reach, and how we keep that boundary secure, spanning OAuth 2.0/2.1 and OIDC, MCP connectors and registries, SAML federation, mTLS, IP allowlisting, and edge/ingress routing (Envoy).
Design and evolve the AI integration architecture – define standards, guardrails, and reusable patterns so onboarding each new AI vendor is fast, consistent, and secure by default rather than a bespoke effort.
Build and own custom MCP servers – develop and operate the connectors that expose internal tools (Slack, Google Workspace, Atlassian, and more), including building new features as internal tools and AI use cases evolve, and integrating AI tools into Pinterest’s skill registry.
Lead incident response and complex, cross‑system troubleshooting for high‑impact integration issues, driving root‑cause analysis, long‑term fixes, and learning‑oriented postmortems in partnership with Security, Networking, and vendors.
Build automation and integrations using scripting (e.g., Python, Go, TypeScript, or similar) and platform/tool APIs and SDKs to streamline connector lifecycle, configuration as code, and health/usage monitoring.
Integrate AI tools with identity, security, and IT workflows (e.g., SSO/IdP, SCIM, DLP, logging, ITSM) in close collaboration with Security and other infrastructure teams.
Use AI as a force multiplier for your work — for example, using AI assistants to draft code, configuration templates, tests, documentation, or runbooks — while validating outputs through tests, dry‑runs, and peer review, and maintaining full ownership of the final results.
Lead cross‑functional projects such as new AI tools onboarding, secure transport/tunnel deployments, connector migrations, and integration‑standard rollouts from design through production.
Mentor and uplevel other engineers by reviewing designs and implementations, sharing best practices, and providing clear guidance aligned to Role Expectations Guides (REGs), leveling criteria, and Pinterest competencies.
Represent the team with stakeholders across the company and with external vendor engineering teams, translating business needs into durable technical solutions, communicating trade‑offs, and ensuring decisions reflect “Act as one” and “Create belonging” for our global workforce.