Search Engineer (Software Engineer III)
Work Authorization: This position does not offer employment visa sponsorship, now or in the future. This includes new H-1B petitions, H-1B transfers, TN, O-1, OPT and green card sponsorship. Applicants must be legally authorized to work in the United States without sponsorship. All hires will be required to complete Form I-9 employment eligibility verification.
ABOUT THE ROLE
We're building intelligent product search that understands intent, learns from behavior, and gets smarter over time. As a Senior Full Stack Engineer on the ML/AI Search team, you'll design and build both the frontend and backend systems that power product discovery for millions of industrial buyers - from scalable retrieval pipelines, APIs, and Frontend interfaces that make AI accessible.
This isn't a research role. You'll own the full lifecycle: prototyping ideas, shipping production-grade services on GCP, and iterating based on real user data. Strong Python and React engineering is the foundation - if you also bring experience in search systems, vector databases, or Elasticsearch, you'll hit the ground running from day one.
WHAT YOU'LL DO
Build & Ship Search and AI-Powered Systems
- Design, develop, and deploy production Python services end-to-end - from retrieval and ranking pipelines through client-facing APIs.
- Build and integrate ML inference pipelines: embedding models, transformer-based classifiers, LLM-powered query understanding, and reranking services.
- Develop event-driven, real-time architectures using GCP services - Cloud Run, Pub/Sub, GKE, Cloud Functions.
- Write clean, well-tested, observable Python backends; own your services through deployment, monitoring, and on-call
- Drive frontend architecture decisions, establishing development standards, and creating reusable component libraries.
Contribute to Search Infrastructure
- Work alongside the Search Architect and ML Architect to implement hybrid retrieval systems combining keyword search, dense vector similarity, and reranking.
- Build and maintain Elasticsearch indexing pipelines, query services, and relevance tuning tooling.
- Integrate vector databases (Pinecone, Weaviate, FAISS or similar) into retrieval workflows - even if this is new territory, you'll learn fast.
- Instrument search pipelines with meaningful metrics: CTR, zero-result rate, latency - feeding the team's A/B experimentation loop.
- Build clean, responsive, and production-ready interfaces from wireframes or Figma designs.
Own the Engineering Bar
- Champion CI/CD, observability, testing, and infrastructure-as-code as non-negotiables, not afterthoughts.
- Lead design sessions with Engineers and Architects; translate product requirements into clean, maintainable technical solutions.
- Participate in code reviews and knowledge-sharing - actively raising the team's collective skill level.
WHAT YOU BRING
Must-Haves
- Strong Python and React foundation: 6+ years of professional backend or full-stack engineering experience with a deep Python/React (e.g., Next.js, Vite.js, Remix.js, Gatsby.js) focus - async patterns, type annotations, testing, and production-grade service/component design.
- Cloud-native experience: Proven experience designing and deploying cloud-native applications (
GCP strongly preferred; AWS or Azure considered).
- Hands-on experience building resilient high throughput microservices and RESTful/gRPC APIs.
- Solid understanding of containerization (Docker), orchestration (Kubernetes), and serverless paradigms.
- Strong grounding in SOLID design principles and software craftsmanship.
- Good communicator who thrives in cross-functional, agile teams alongside ML engineers, architects, and product owners.
- Comfort using AI tools to accelerate development throughput.
- Strong experience of using and managing Monorepos
- Strong understanding of relational (e.g., PostgreSQL, MySQL, Oracle) and non-relational databases (e.g., MongoDB, DynamoDB).
- Mentorship: Provide guidance and technical knowledge sharing to mid-level and junior developers.
Strongly Preferred - Search & ML
You don't need all of these on day one - but the more you bring, the faster you'll contribute:
- Search systems: Experience with search platforms:
Elasticsearch, OpenSearch, Solr, or Algolia - index management, query DSL, relevance tuning.
- Vector search: Familiarity with vector search concepts and tooling:
embeddings, approximate nearest neighbor (ANN), FAISS, Pinecone, Weaviate, or similar.
- Exposure to ML/AI patterns: RAG pipelines, LLM integration, prompt engineering, or fine-tuning workflows.
- Experience with AI orchestration frameworks such as LangChain, LangGraph, or Google ADK.
- Infrastructure-as-code experience (Terraform, Pulumi, OpenTofu) and mature CI/CD pipeline ownership.
WHO YOU ARE
Fearless Builder
A working proof-of-concept beats a thousand slide decks. Speed and quality are both non-negotiable.
Relentless Learner
You pick up new technologies fast and have a genuine eagerness to master whatever comes next.
Architecture-Minded
You design scalable, fault-tolerant services as second nature and aren't afraid to challenge the status quo.
Ownership-Driven
Code isn't done until it's tested, documented, and monitored. Your name on a release means something.
Search-Curious
You may not have built a search system yet - but you're excited by the challenge and ready to go deep.
Team Multiplier
You give and welcome candid feedback and actively make the people around you better.