About the role

Matching our experts with the right opportunities is at the heart of our business. It spans search, discovery, recommendations, ranking, and the ontology that ties everything together.

We're looking for a senior engineer to own this area of our stack. You'll take end-to-end ownership of how we surface and match the right experts to each customer's need: the data and indices behind it, the relevance and ranking that make results feel obvious, and the discovery experiences our customers rely on every day. It's a backend-leaning, full-stack role with real influence over architecture, product direction, and how we ship.

You don't need to be a search specialist on day one. We're looking for a strong senior generalist who knows enough about search and relevance to make an immediate impact, and who wants the runway to go deep and own this domain as it grows. If you've built search, discovery, or recommendation features and want to make them your craft, this is a rare chance to own the problem end to end.
What you'll do

• Own search, discovery, and recommendations end to end, from the underlying data and indices to relevance, ranking, and the user-facing experience
• Build and improve the backend services and APIs that power matching across our knowledge graph, with a focus on precision, recall, and performance
• Turn fragmented, unstructured data into structured, searchable knowledge through reliable ingestion and indexing pipelines
• Ship user-facing search and discovery features across the stack, partnering closely with product and design
• Raise the bar on architecture, code quality, and observability as you scale this part of the platform
• Explore AI and LLM-assisted approaches to discovery (retrieval, embeddings, ranking, agentic workflows) and bring the promising ones to production

What you bring

• 6+ years of software engineering experience, with strong backend fundamentals and comfort working across the stack
• Pride in your craft and a track record of shipping high-quality products and features at scale
• Experience with search, discovery, recommendations, or data-intensive systems, and enough knowledge of relevance and ranking to make an immediate impact
• The ability to turn ambiguous user and business problems into clean, scalable, well-tested engineering solutions
• A self-starter mindset, with the desire to own a domain end to end and grow into deeper ownership of it over time

Tech Stack

• Back end: Node.js, TypeScript, MongoDB, OpenAPI, RabbitMQ, Elasticsearch
• Infrastructure: AWS, Kubernetes, Docker, Terraform, Kibana, Sentry
• Workflow: GitHub, Slack, Notion, Figma, Amplitude, Storybook
• Front end (not required for this role): React, Next.js, Tailwind

Bonus Experience

• Deep experience with search relevance and ranking, including precision/recall tradeoffs, retrieval, and reranking
• Experience building recommendation systems or personalization at scale
• Familiarity with vector or semantic search (embeddings, HNSW/IVF, hybrid retrieval)
• Experience with knowledge graphs or entity resolution
• You've integrated LLMs into search or discovery workflows in production
• Experience with data-intensive, event-driven, or asynchronous processing systems

Benefits + Perks

• Competitive salary and equity
• Medical, dental, and vision coverage
• 401(k)
• Monthly wellness and fitness stipend
• Paid time off policy, along with company holidays
• Annual company off-sites (Tahoe, Mendocino, Mexico City, San Diego, Park City)
• Parent-friendly policies, remote flexibility, and paid family leave

Pay Transparency Notice

Full-time offers include base salary, equity, and benefits.

Pay range: $170,000-$220,000, based on seniority and relevant experience

This role is San Francisco-based preferred (2-3 days per week in office), and open to fully remote for the right candidate.