This role pays more than
89%
of similar roles. Most pay
$141,383–$208,830
— the shaded band above.
At the midpoint, this role pays about
$225k
versus about
$175k
for comparable roles.
Based on 240 similar postings.
Employer
About Balyasny Asset Management
Balyasny Asset Management (BAM) is a global multi-manager hedge fund offering diversified investment strategies across equities, macro, commodities, and systematic trading.
Balyasny Asset Management currently has
47 open roles
on FindRole.
Listed pay typically runs
$175,000–$242,500
across 26 roles with salary data.
As the Macro AI Engineering Lead at BAM’s Macro and Fixed Income team, you will build and manage a specialized team of AI Engineers embedding directly with portfolio managers, traders, analysts, and specialists to accelerate adoption of in-house generative AI and data science products. Your daily responsibilities include designing scalable technical architectures, fostering a strong engineering culture, and establishing feedback loops with BAM’s Data Science and AI teams. You will also partner with senior leadership to develop strategic roadmaps for AI adoption, track emerging LLM techniques, and pilot innovative solutions tailored to Macro and Fixed Income use cases. The ideal candidate has over 10 years of experience in customer-facing roles, including at least five years in leadership positions managing software engineering teams focused on LLM-based and data science solutions. Expertise in Python, SQL, cloud platforms (AWS preferred), containerization, orchestration, vector databases, and RAG systems is essential, along with a deep understanding of macroeconomic and Fixed Income analysis.
Lead the development of a specialized team of AI Engineers focused on Macro and Fixed Income markets.
Design scalable technical solutions to maximize the value of BAM’s AI tools for global market strategies.
Embed with key trading desks to drive strategic adoption of generative AI and data science tools.
Translate high-level investment strategy requirements into technical solutions addressing complex challenges in global markets.
Track emerging LLM techniques and pilot promising innovations, leading their adoption across the platform.
What we're looking for
10+ years of experience in customer-facing roles, including at least 5 years in leadership positions managing software engineering teams focused on LLM-based solutions.
Proven track record of building and scaling AI/ML teams and driving enterprise-wide technology adoption in financial services.
Demonstrable experience architecting and deploying large language model (LLM)-based applications at scale.
Strong preference for candidates with significant Macro, Fixed Income, or rates experience, including hands-on economic analysis and direct leadership collaboration with portfolio managers.
Expert-level proficiency in Python & SQL for data manipulation, statistical modeling, and machine learning.
Familiarity with containerization (Docker), orchestration (Kubernetes), cloud platforms (AWS preferred), vector databases, and RAG systems.
Advanced academic training in computer science, statistics, data science techniques, and generative AI methods.