AI Native Engineer

Legalist•New York, NY

8h•Hybrid

About The Position

Legalist is a tech-enabled alternative asset manager that uses proprietary data-driven origination to invest in uncorrelated legal and government-payment assets. Founded out of Y Combinator in 2016, Legalist manages over $1.7 billion for endowments, foundations, and family offices. Legalist is looking for an AI Native Engineer to join our team and work directly with our Co-founder to build AI-powered products and workflows. This is a hands-on, execution-focused role for someone who has a track record of building across a variety of projects and is already using AI as a core part of how they develop software. Our ideal candidate operates in a fast-paced environment and can take a business problem or idea, figure out the technical approach, build a solution, and iterate quickly.

Requirements

3+ years of professional software development experience
Hands-on experience building applications with LLM APIs such as OpenAI, Anthropic, or similar
Experience building AI agents, tool-calling workflows, or other agentic systems
Strong understanding of APIs, backend development, databases, and cloud infrastructure
Experience taking software from prototype through production
Experience working with financial, legal, or other complex datasets
Familiarity with prompt design, context management, model evaluation, and techniques for improving LLM reliability
Experience working across a variety of technical projects, ideally for multiple companies or clients
Comfortable working independently and figuring things out without a detailed set of requirements

Nice To Haves

Local to New York City and excited about the opportunity to have regular in-person working sessions

Responsibilities

Design and build new AI products, tools, and features
Build applications using LLMs and foundation model APIs
Develop AI agents and multi-step workflows that connect models with internal and external systems
Build integrations with third-party APIs, internal data sources, and existing software
Design and implement RAG pipelines, including retrieval, embeddings, vector search, and context management
Build backend services and APIs to support AI applications
Prototype new ideas quickly, thoroughly test them, and turn successful prototypes into production-ready tools
Evaluate models and approaches based on accuracy, latency, cost, and reliability
Build evaluations and testing processes to measure and improve model outputs
Stay current on new models, developer tools, frameworks, and AI capabilities