Senior / Staff Software Engineer (Search)
Company: Career Mentors
Location: New York, NY
Salary: $190,000 - $220,000 a year
Type: Full-time
Posted: 2026-03-12
About this role
### Senior / Staff Software Engineer (Search)
Location: New York, NY (Full-time, on-site 5 days/week) Compensation: $190,000 – $220,000 base + competitive equity
Hiring: 1–2 candidates ASAP
The Role Greenfield opportunity to build search, recommendation, and knowledge systems from the ground up. Backend-leaning role focused on designing and scaling intelligent retrieval pipelines, data engineering, and AI-driven discovery across massive, messy document sets.
Key Responsibilities
- Design, build, and scale backend services that power search, recommendations, and relevant data retrieval.
- Build and optimize data pipelines to ingest, normalize, and index large volumes of government and enterprise data.
- Create retrieval pipelines using embeddings to search and reason across thousands of documents (vector search, semantic retrieval).
- Solve entity resolution challenges across messy, real-world datasets — de-duplication, merging, cleaning, structuring.
- Own projects end-to-end: from technical design and implementation through deployment and iteration.
- Collaborate closely with product and engineering teams to deliver data-driven features.
- 5+ years of professional software engineering experience.
- Experience building search systems, data pipelines, or recommendation systems at a startup (ideally Series B/C).
- Background in data science, information retrieval, or recommendation systems.
- Hands-on experience with embeddings, vector search, or RAG.
- Strong backend development expertise with TypeScript / Node.js.
- Comfort working with large, messy, real-world datasets.
- PhD or Master's in Machine Learning or related field (higher studies can offset some years of experience).
- Self-starter with an ownership mentality who thrives in a fast-paced startup environment.
- Must be a US Person per ITAR.
#### Traits to Avoid **Candidates with no industry experience (purely academic PhDs); candidates siloed in one function at large t...