Office Hours is an on-demand expert network that connects leading organizations with trusted experts across various knowledge domains. Experts earn income by sharing their knowledge through advisory work, projects, and AI model training. Our platform handles the complexities behind the scenes— screening, compliance, scheduling, and payments—so knowledge sharing stays focused on meaningful insights and real impact.
We're a hyper-growth and profitable company, quickly expanding our expert network, launching new offices, and new products. We are headquartered in San Francisco, with offices in Brooklyn and Bangalore. Our customers include the fastest-growing digital health companies, technology companies, institutional investment firms, consulting firms and AI Labs. We are backed by top marketplace investors and operators of companies like DoorDash, Airbnb, Affirm.
What we believeHuman knowledge is the world's most valuable asset. And yet, despite being more interconnected than ever, most knowledge still remains stuck in our heads, inaccessible and underutilized. Our vision is to make human knowledge easily accessible and infinitely scalable by building tools for the new age knowledge economy.
About the roleMatching 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 doOwn 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
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
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
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
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.
Don't meet every single requirement? Studies have shown that some candidates, especially underrepresented groups such as women and people of color, are less likely to apply to jobs unless they meet every single qualification. At Office Hours we believe in building a diverse and inclusive workplace, so if you're excited about this role but don't meet every qualification in the job description, we still encourage you to apply. You could still be the right candidate for this or other roles at Office Hours!
