Quant jobs / Balyasny Asset Management

AI Engineer, Multi-Asset Arbitrage

The multi-asset arbitrage and credit organisation is building AI tools for investment analysis and risk work. The engineer owns applications from initial prototype to monitored production use.

What you’d work on

Our reading of the posting: what a new hire in this role would most likely spend their first months on.

Build research data pipelines and APIs
Integrate document retrieval and structured extraction
Evaluate accuracy and preserve source references
Deploy applications with monitoring and access controls

What they ask for

Required

Three or more years of production software work
Python or Rust plus SQL
API design and testing
LLM integration and evaluation
Data structures and system design
Explaining technical trade-offs

Preferred

Production retrieval or agent applications
Financial datasets
Cloud deployment
FastAPI/React
Vector or graph databases

Education: Computing, maths, statistics or related master study; equivalent experience is accepted.
Experience: 3+ years of software or quantitative development/research, including production delivery.
Languages and tools: Python
Rust
SQL
Markets: credit, multi-asset

How to prepare

Build a cited document-retrieval prototype and measure accuracy
Demonstrate a tested API around structured extraction
Explain how to monitor and recover a production AI workflow

What to study

The NLP and ML Quant Researcher roadmap sets out the stages for this kind of role, with free resources for each.

Open the roadmap

Apply

Read the full posting on Balyasny Asset Management’s site before applying: requirements, location and pay can change after we check them.

View the posting on Balyasny Asset Management’s site ↗

SelfMadeQuant wrote this summary from the employer’s public posting, last checked 6 November 2026. SelfMadeQuant isn’t affiliated with Balyasny Asset Management and doesn’t handle applications.