Software Engineer, Applied AI

Responsibilities

• Build and integrate LLM-backed workflows, including prompt systems, retrieval, memory, evaluation, and feedback loops.
• Develop new AI workflows and systems that make cutting-edge AI available across the platform.
• Regularly contribute performant, high-quality code to the production codebase.
• Oversee data collection, experimentation, and data analysis to continuously improve the platform, working closely with domain experts.
• Build comprehensive benchmarks and evaluation suites to measure AI agent performance and guide future improvements.
• Architect the system of underlying prompts that power AI agents, engineering effective context structures and automated pipelines for prompt optimization.
• Enable continuous learning in AI agents through memory, feedback, and client-specific preferences.
• Develop legal and compliance domain expertise.

Requirements

• 4+ years of experience as a software engineer, applied AI engineer, ML engineer, or data scientist.
• Strong programming skills in Python.
• Proficiency in Docker and data storage technologies such as Postgres and Redis.
• Experience working with production systems, including debugging, monitoring, and iterating on live software.
• Willingness to work with frontend technologies (Typescript, React, etc.) to bridge research ideas and productization.
• Experience in AI/ML infrastructure and tooling.
• Experience integrating AI or ML components into real-world systems (LLMs, classical ML, or hybrid approaches).
• Interest in becoming a legal and compliance domain expert and working closely with professionals in the field.
• Strong reading, writing, and quantitative skills, as well as a data-driven approach to problem solving.
• AI fluency: actively use AI in day-to-day work with concrete examples of tools, workflows, and outcomes.

Nice-to-Haves

• Familiarity with and an eagerness to apply the latest AI research.
• Experience applying traditional ML systems and processes in the context of state-of-the-art LLMs.
• Experience deriving insights from PDFs and other unstructured or semi-structured data types.
• Experience with context engineering and memory in the context of AI agents.
• Experience modeling uncertainty in ML systems.

Compensation and Benefits

• Senior Engineer: $190,000 - $250,000 per year + equity
• Staff Engineer: $240,000 - $280,000 per year + equity
• Competitive salary with equity compensation.
• Comprehensive benefits: 401(k) with employer match, top-tier health, dental, hospital, accident, and vision insurance.
• Relocation reimbursement for candidates moving to NYC.
• Flexible hybrid model (typically in-office 3–4 days per week).