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AI Engineer (Data & Infrastructure)

brightplace
Full Timemid
US$149k – $179kPosted March 1, 2026

Salary Context

This role offers $149k–$179k. The median for Mid-level backend roles is $100k–$160k (based on 44 listings). 26% above median.

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PythonSQLGraphQLDjangoFastAPIAWSGCPAzureAPI

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Job Description

We're looking for an AI Engineer who thrives at the intersection of data, APIs, and intelligent systems. You'll own the backend infrastructure that powers our AI-first platform, from data acquisition and normalization to API design and system architecture. This is a founding engineer role where your decisions will shape our technical foundation.

You'll focus on:

  • Designing and building data pipelines that transform diverse sources into clean, queryable datasets
  • Creating robust APIs that serve both internal AI systems and external partners
  • Architecting backend services that handle high-volume, real-time data processing
  • Partner with other engineers to build a seamless full-stack product
  • Shipping features quickly, learning from real usage, and iterating

WHAT WE ARE LOOKING FOR:

Technical foundation:

  • 5-8 years building production systems with modern Python (FastAPI, Django, or similar)
  • Strong experience with data extraction, normalization, and database design (SQL + NoSQL)
  • Proven ability to design and scale RESTful or GraphQL APIs
  • Comfort with cloud infrastructure (AWS, GCP, or Azure)
  • Real experience integrating LLMs into production systems (not just experiments)

AI-first mindset:

  • You default to using AI tools (Claude, Cursor, Copilot) to accelerate development
  • You think about how to build systems that get smarter with data
  • You're excited about prompt engineering, embeddings, and working with unstructured data

Startup DNA:

  • Early-stage company experience required
  • Ship fast, learn from production, iterate based on data
  • Thrive in ambiguity and make smart trade-offs without perfect specs

WHAT WE VALUE:

  • Velocity over perfection: We'd rather ship and learn than build the "right" architecture in a vacuum
  • Ownership: You'll own significant parts of the product: autonomy and accountability
  • AI-native thinking: We're building for an AI-first world, not bolting AI onto old patterns
  • Pragmatism: Use the right tool for the job, even if it's not the coolest technology

NOTE:

  • Candidates outside of NYC are not being considered
  • We are unable to provide sponsorship for this role

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