AI Engineer (Python, LLM APIs, Cloud Infra) - USA Remote

  • Contract

Job Description

AI Engineer (Python, LLM APIs, Cloud Infra)

  • Location: Remote, USA Only
  • YoE: 5+
  • Project duration: 12+ month
  • Full-time dedication (40 hours/week)
  • Start Date: Immediately
  • Rate Range: Competitve, TBD

Company Overview:

Our client is ​​​​one of the world's fastest-growing AI companies accelerating the advancement and deployment of powerful AI systems. They help customers in two ways: Working with the world’s leading AI labs to advance frontier model capabilities in thinking, reasoning, coding, agentic behavior, multimodality, multilinguality, STEM and frontier knowledge; and leveraging that work to build real-world AI systems that solve mission-critical priorities for companies.

​​​​​About the Role:

​​​​​​​An early-stage startup is redefining how financial research is conducted by creating a declarative orchestration layer akin to "Vercel for financial research." This backend engineering role focuses on simplifying the infrastructure behind large language model (LLM) integrations, runtime orchestration, and data workflows. You'll work at the intersection of LLM tooling, serverless infrastructure, and financial data systems to make spawning new research pipelines seamless and scalable.

Required Skills:

  • Strong Python programming experience
  • Proficiency with cloud infrastructure and serverless compute (e.g., Modal)
  • Familiarity with relational databases such as PostgreSQL
  • Experience integrating with LLM APIs (OpenAI, Anthropic, xAI, Google) or LLM frameworks (e.g., PydanticAI)
  • Ability to work autonomously and quickly adapt to evolving tech stacks
  • Excellent problem-solving skills and a builder’s mindset

Bonus Skills

  • Prior experience with financial data APIs (e.g., S&P, FactSet, SEC Edgar)
  • Familiarity with AI tooling APIs (e.g., Exa, Parallel)
  • Previous successful engagements with other clients in similar contractor roles

Offer Details

  • Contractor position (no medical/paid leave)
  • Full-time dedication (40 hours/week)

Additional Information

All your information will be kept confidential according to EEO guidelines.

I'm interested