Who will love this job

1. An adaptable contributor – you adjust quickly to changing needs and stay effective in dynamic environments
2. A pragmatic architect – you evaluate trade-offs between performance, relevance, maintainability, and cost, choosing patterns that simplify complexity for the long term
3. A problem solver – you think about the bigger picture, connect the dots, and efficiently resolve technical and product challenges
4. An excellent communicator – you explain technical processes clearly, including to non-engineers, and work well with Product, Design, Data, and Applied ML partners
5. A search and matching builder – you enjoy turning complex retrieval and ranking problems into intuitive, trustworthy product experiences

What you’ll do

1. Collaborate with Product Managers and Designers to define requirements and build product experiences from conception through delivery
2. Build and improve full-stack experiences for Talent Matching, Talent Rediscovery, and related talent discovery workflows
3. Design and ship search-backed capabilities using OpenSearch or Elasticsearch, including indexing, query design, relevance tuning, ranking, and semantic retrieval
4. Develop matching systems that combine keyword, structured, semantic, and AI/ML signals to improve match quality
5. Partner with Applied ML and cross-functional engineering teams to evaluate trade-offs across relevance, latency, reliability, infrastructure cost, and user trust
6. Build evaluation, observability, testing, and feedback mechanisms to continuously improve matching quality
7. Develop clean, efficient, maintainable, and scalable production code for core services
8. Contribute to code reviews and engineering practices
9. Additional projects as needed within the scope of the engagement

You should have

1. 5+ years of experience writing production code
2. Experience with Ruby, C#, Java, or Python; Ruby on Rails preferred
3. Strong JavaScript or TypeScript fundamentals, including React
4. Full-stack experience across backend systems, APIs, data modeling, and modern frontend development
5. Deep experience with OpenSearch or Elasticsearch in production, including indexing, query design, relevance tuning, and performance trade-offs
6. Experience building search, ranking, recommendation, or matching systems
7. Practical experience applying AI or ML techniques in production, such as embeddings, semantic search, classification, or ranking
8. Experience collaborating with Product and Design in ambiguous, user-facing problem spaces
9. Experience with analytical databases, a plus
10. Your own unique talents! Your background has given you a unique perspective and set of transferable skills that aren't always in alignment with a given role - but those are qualities we value here. If you don't meet 100% of the qualifications outlined above, we still strongly encourage you to apply