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...

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