СШАStaff Engineer, Applied AI
3 дн. назад
225k–265k USD / годСШАLeadOnsite
Staff Engineer position focused on applied AI at , contributing to AI and ML solutions for dating platforms.
О компании
- Our Mission As humans, there are few things more exciting than meeting someone new. At Tinder, we’re inspired by the challenge of keeping the magic of human connection alive. With tens of millions of users, hundreds of millions of downloads, 2+ billion swipes per day, 20+ million matches per day, and a presence in 190+ countries, our reach is expansive—and rapidly growing. We work together to solve complex problems. Behind the simplicity of every match, we think deeply about human relationships, behavioral science, network economics, AI and ML, online and real-world safety, cultural nuances, loneliness, love, sex, and more. Our Values Take the Lead: We don't ghost our work or each other. Just as users don't leave their matches hanging, we don't let each other down. Move Fast: We have a bias for action and urgency. Something that could be done tomorrow would be better if done today. Better Together: We keep connection at the heart of dating and at the heart of how we work. Just as our users are better when they connect with others, so are we when we collaborate. Real Talk: We say the hard thing the human way. Just as we ask our users to behave with kindness and candor in our community, we expect Team Tinder to do the same. Safety First: We act with integrity, transparency, and consistency so people feel safe—whether they're swiping, matching, or working alongside us. Spark Fun: We have fun to unlock creativity, fuel innovation, and help us build better experiences for daters.
Обязанности
- Work closely with internal teams to build real solutions for challenges they are facing day to day.
- Own the design of the agent platform across gateway, connectors, identity, policy, guardrails, observability and cost, and write the roadmap for how it evolves.
- Design identity and delegation for agents: acting on behalf of a user, agent-owned identities for unattended jobs, short-lived scoped credentials, and every action traceable to a responsible human.
- Build access control beyond tool allowlists: per-action, per-argument and per-data-class policy, human approval for irreversible actions, and policy that's reviewable and tested.
- Build guardrails enforced at the tool boundary, not in prompts, against prompt injection through tool output, confused-deputy access, data exfiltration and over-broad scopes.
- Make agent behavior observable: traces of tool calls and decisions, audit trails investigators can use, evals that catch regressions when models or prompts change, and per-team cost attribution.
- Set the bar for connectors and third-party MCP servers: onboarding, review, versioning, sandboxing and safe defaults.
- Run the platform as production and own its on-call: latency budgets, failure modes, rate limits and quotas, kill switches and incident response.
- Partner with Security, our forward deployed engineers and platform teams, and mentor the engineers who build on and contribute to the platform.
Будет плюсом
- Experience with policy engines or workload identity.
- Built or operated an LLM gateway, model router or MCP server in production.
- Familiarity with OpenTelemetry and tracing for non-deterministic systems.
- Contributions to agent identity or MCP authorization standards.
- Engineering background in application protection, identity and access management, or threat detection and incident response.
Другое
- Great communication and collaboration skills, experience working with real challenges of customer
- 8+ years building backend, infrastructure or platform systems that other teams depend on, with recent hands-on work on LLM agents, tool use or MCP.
- Experience shipping identity or authorization systems: OAuth 2.0 and OIDC, token exchange or delegation, service identity, and policy models (RBAC, ABAC or relationship-based).
- An attacker's mindset about agent systems, and the ability to explain why prompt-level defenses aren't enough.
- Experience operating gateways, proxies or other services in the critical request path, including on-call, observability and incident response.
- Strong skills in Python or TypeScript, and daily use of AI coding tools with a clear sense of where they fail.
- A track record of working well with security teams and impatient internal customers, turning "no" into a safe "yes, like this."