Applied AI Scientist – AI Fellowship Program

Balyasny Asset Management L.P.; New York (NY); On-site; USD 90,000 - 130,000; Full time

Job summary

Balyasny Asset Management L.P. invites applications for its exclusive AI Fellowship, a rotational program embedding elite AI practitioners with BAM’s investment teams in New York.

You will start with the central AI team, learning BAM’s platform and shipping production tooling, then rotate to work directly with portfolio managers on agentic workflows and research automation. Qualifications include a Master’s in a quantitative field and hands-on experience building LLM-based apps in production.

Qualifications

• Master's degree or equivalent in a quantitative field with strong CS and ML foundations.
• Proven experience building LLM-based applications in production.
• Experience translating complex investment workflows for non-technical stakeholders.

Responsibilities

• Build agentic workflows, data pipelines and research automation for investment teams.
• Embed with PMs and analysts to translate requirements into technical solutions.
• Learn BAM's AI platform and contribute production tooling to central platform.
• Rotate across investment teams to find high-impact problems.
• Track and apply emerging LLM techniques and agentic frameworks.

Skills

Python programming

LLM-based solutions

Communication with stakeholders

Ambiguity management

Education

Master's degree in AI/Data Science/CS/Statistics/Math

Advanced degrees preferred

Tools

OpenAI API

Anthropic API

Google API

LangGraph

OpenAI Agents SDK

Claude Agent SDK

Codex

AWS

Azure

GCP

Airflow

Git

Job description

BAM is launching an exclusive AI Fellowship program – a rotational program that places elite AI implementation talent directly onto BAM’s investment teams. You will begin embedded with our central AI team, learning BAM’s platform and systems while shipping production tooling from the outset. You will then rotate onto investment teams as the dedicated AI partner to a portfolio manager, building agentic workflows, research automation, screening tools and model tooling against live investment problems. Teams have already signalled demand for these seats, and the goal is a permanent home on the desk.

Key Responsibilities

Build for the Desk: Design, build and deploy agentic workflows, data pipelines and research automation that directly improve a portfolio manager’s research process and decision speed

Learn the Platform: Spend your initial months with the central AI team mastering BAM’s in-house AI ecosystem, while contributing production tooling to the central platform

Embed & Partner: Sit with PMs and analysts on rotation, translating investment workflows and ambiguous requirements into working technical solutions

Rotate & Explore: Work across multiple investment teams and strategies, developing the breadth of exposure needed to find the team and problem set where you have the greatest impact

Maintain Edge: Track emerging LLM techniques and agentic frameworks, pilot promising approaches on real investment problems, and bring proven wins to the teams you work with

Qualifications

Education

Master's degree in AI, Data Science, Computer Science, Statistics, Mathematics or a related quantitative field, or equivalent work experience. Advanced degrees preferred

Strong grounding in computer science, statistics, machine learning and generative AI is required

Experience

3 – 5 years of experience in a user-facing role, scoping, building and deploying LLM-based solutions in production

Demonstrable experience building LLM-based applications using agentic frameworks

Direct work with non-technical stakeholders to shape and deliver solutions

Exposure to buy‑side, equity research or another investment setting is a plus

Technical Skills

Highly proficient in Python for engineering, statistical modelling and machine learning

Experience integrating LLMs and AI models into production workflows

Familiarity with model provider APIs (OpenAI, Anthropic, Google) and agentic frameworks such as LangGraph, the OpenAI Agents SDK or the Claude Agent SDK

Fluency with agentic coding tools such as Claude Code and Codex

Working knowledge of MCP for tool and data integration

Familiarity with cloud platforms (AWS, Azure, GCP), Git, and workflow orchestration tools such as Airflow is a strong plus

Soft Skills

Strong problem-solving and analytical skills, with a bias toward shipping

Excellent communication skills; able to explain technical trade-offs to portfolio managers and analysts

Self-directed, comfortable operating with ambiguity and limited supervision

Able to manage multiple workstreams and deliver to deadline