Staff AI Engineer, Trust & Safety Operations

Hinge is the dating app designed to be deleted

In today's digital world, finding genuine relationships is tougher than ever. At Hinge, we're on a mission to inspire intimate connection to create a less lonely world. We're obsessed with understanding our users' behaviors to help them find love, and our success is defined by one simple metric-- setting up great dates. With tens of millions of users across the globe, we've become the most trusted way to find a relationship, for all.

About the Role

Join Hinge as a Staff AI Engineer for Trust & Safety Operations, where you'll lay the cornerstone of our agent-powered future. You will architect the foundational workflows, guardrails, and tooling that turn AI agents into everyday teammates for our Moderation, Appeals, and Support operators. Think of it as building the "operating system" for AI within Trust & Safety: establishing the orchestration layer, standardizing tool schemas, automating the agent lifecycle, instrumenting real-time monitoring, and ensuring every solution is robust, scalable, efficient, and responsible. You'll collaborate closely with operations professionals and engineers, meet non-technical stakeholders where they are, and deliver value in tight, incremental loops tied directly to solving their biggest problems. Because we're still early in our agent journey, you'll enjoy a broad scope with an expectation of mentoring peers, shaping best practices, and defining the north star for AI-native operations at Hinge. If you're energized by building green-field systems that leverage AI to solve challenging problems, this is your invitation to help write the next chapter of Trust & Safety to create a safer and more meaningful user experience on their journey to find an intimate connection.

Responsibilities

• Own the technical roadmap for AI automation across Moderation, Appeals, and Support workflows, driving discovery and prioritization of high-impact AI automation opportunities while providing hands-on technical leadership from concept to production.
• Prototype agentic solutions using the latest platforms and frameworks and integrate them with existing internal and third-party tools and systems.
• Deliver reliable, scalable, and robust automations with the appropriate evaluations, guardrails, human oversight, and clear performance monitoring.
• Drive adoption by producing documentation, running hands-on training and enablement sessions for non-technical operators, and curating prompt libraries and playbooks that empower self-service iteration.
• Collaborate closely with Data Scientists, Data Engineers, Product Managers, Backend Engineers, and the AI Platform Team to ensure a comprehensive and coordinated approach to improving operational efficiency.
• Embed safety, privacy, auditability, and responsible-AI standards into every workflow in partnership with Legal and Security teams.
• Mentor and educate ML Engineers and Platform Engineers on new trends and research in AI/ML that can be applied to Trust & Safety initiatives to promote user safety and improve AI-powered products and workflows.

What We're Looking For

• Agentic & workflow-orchestration expertise: Proven ability to design, build, and operate multi-step LLM agents with modern coordination frameworks.
• Applied AI engineering & prompt craft: Deep Python skills plus hands-on experience integrating foundation models and crafting robust prompts and utilizing vector databases.
• **Rapid prototyping & experimentation:**Comfortable shipping quick proofs of concept, running A/B or shadow launches, and iterating based on data.
• Backend, data-systems & tool integration: Skilled at wiring external services and internal data into agent workflows through well-designed APIs and schemas.
• Human-in-the-loop system design: Able to blend automation with human oversight through clear escalation paths, review checkpoints, and moderator tooling.
• **Operator enablement & training:**Talent for translating technical workflows into clear, actionable training for non-technical teams and supporting their day-to-day adoption.
• **Working through ambiguity:**Proven skill thriving in high-ambiguity, fast-moving environments---prioritizing effectively, adapting plans quickly, and delivering impact amid shifting requirements.

Prior Experience

• 7+ years of software or machine-learning engineering experience, with a recent focus on AI-driven automation or agentic systems.
• 2+ years delivering solutions that combine automated decision support with human-in-the-loop review, ideally in Trust & Safety, customer support, or adjacent domains.
• 2+ years designing and tracking operational metrics that demonstrate ROI, accuracy, and user-experience improvements for automated workflows.
• 1+ years of hands-on work prototyping or operating agentic workflows (e.g., MCP, Agentspace, n8n) in real-world or open-source projects.
• A degree in computer science, engineering, or a related field (or equivalent practical experience).
  $244,000 - $293,000 a year Factors such as scope and responsibilities of the position, candidate's work experience, education/training, job-related skills, internal peer equity, as well as market and business considerations may influence base pay offered. This salary range is reflective of a position based in New York City. This salary will be subject to a geographic adjustment (according to a specific city and state), if an authorization is granted to work outside of the location listed in this posting.