Job: Senior Full-Stack Engineer (Search, AI & Member-Facing Applications)

About The Role

As a Senior Full-Stack Engineer, you will design, develop, and optimize our client search and discovery experience. You will build and scale AI-powered search features, improving relevance, ranking, personalization, and user experience.

What You’ll Do

• Architect & Build: Design and develop a high-performance search experience for users looking up healthcare procedures.
• AI-Powered Search: Implement ML-driven ranking, embeddings, personalization, and intelligent autocomplete to improve search results.
• Full-Stack Development: Work across the stack, from backend APIs and search indexing to front-end UI components.
• AI Agents & NLP: Use LLMs, embeddings, and AI-driven query understanding to enhance search intent and accuracy.
• Scalability & Performance: Ensure our client search and data processing pipelines scale efficiently and deliver results fast.
• Data-Driven Decisions: Implement analytics, A/B testing, and AI model evaluations to refine search algorithms.
• Collaborate: Work closely with AI/ML engineers, designers, and product managers to build a seamless, intelligent search experience.
• Tech Stack: Ruby on Rails (de-commissioning shortly), React, TypeScript, Node.js, Python, Elasticsearch (or OpenSearch), PostgreSQL, AWS, LangChain, and vector databases (e.g., Pinecone, Weaviate, FAISS).

Who You Are

• 6+ years of full-stack engineering experience, with a strong focus on search-driven applications.
• Expertise in search technologies (e.g., Elasticsearch, OpenSearch, Solr, Meilisearch, or similar).
• Strong frontend experience with modern frameworks like React/Next.js.
• Proficiency in backend development using Node.js, and Python, with experience in building APIs.
• Experience with AI/ML models, including search relevance ranking, NLP techniques, embeddings, and vector-based retrieval.
• Hands-on experience with AI-powered search, LLM-powered query understanding, or intelligent agents.
• Strong understanding of search ranking algorithms, NLP, embeddings, and ML-powered personalization.
• Experience working with large-scale datasets, search indexing strategies, and cloud infrastructure (AWS, GCP, or Azure).
• Bonus: Experience in healthcare data, pricing transparency, or medical procedure search.