Summary
The Macro and Fixed Income team is central to BAM's continued leadership in global markets. As macroeconomic and Fixed Income investing becomes increasingly data-driven, the ability to harness advanced analytics and AI is critical to the team's success. Our group is at the forefront of this evolution, delivering innovative AI and data solutions that empower portfolio managers, analysts, and researchers to make more informed decisions in rates, FX, credit, and related markets. By developing and deploying state-of-the-art AI systems, we help BAM capitalize on emerging opportunities, manage risk, and maintain a competitive edge in the rapidly changing Macro and Fixed Income landscape.
Role Overview
The Macro and Fixed Income organization is building an elite AI enablement team to accelerate adoption of BAM's in-house generative AI and data science products across Macro and Fixed Income investment strategies. In this leadership role, you will build and manage a specialized team of AI Engineers that embeds directly with Macro portfolio managers, rates traders, credit analysts, and FX specialists, while personally driving strategic initiatives that measurably improve decision speed and research processes in global markets. You will serve as the strategic "last mile" between our platform and the Macro and Fixed Income investment organization – leading adoption of in-house tools, architecting agentic workflows tailored to Macro and Fixed Income use cases, and establishing comprehensive feedback loops with BAM's Data Science and AI teams.
Key Responsibilities
• Lead Team & Strategy: Build, manage, and mentor a team of AI Engineers focused on Macro and Fixed Income markets, while developing enterprise-wide adoption strategies across rates, credit, FX, and Macro trading desks
• Technical Leadership: Design and lead the execution of a robust and scalable functional architecture to maximize the value of BAM's AI tools for the Macro and Fixed Income business. Build a strong technical culture within the Macro AI team reinforcing world-class engineering practices and strong accountability to key business stakeholders.
• Drive Strategic Adoption: Partner with Macro and Fixed Income leadership to establish firm-wide AI adoption roadmaps and success metrics, embedding with key trading desks to maximize value from BAM's generative AI and data science tools
• Strategic Partnership: Collaborate with senior Macro PMs and analysts to translate high-level investment strategy requirements into scalable technical solutions that address complex challenges in global markets and Fixed Income investing
• Innovation: Track emerging LLM techniques and machine learning methods relevant to Macro and Fixed Income markets, pilot promising innovations, and lead adoption of proven methodologies across the platform
Qualifications
Experience:
• 10+ years of experience in customer-facing roles, with at least 5 years in leadership positions managing software engineering teams focused on LLM-based and data science solutions
• Proven track record of building and scaling AI/ML teams and driving enterprise-wide technology adoption in financial services
• Candidates must have demonstrable experience architecting and deploying LLM-based applications at scale
• Strong preference for candidates with significant Macro, Fixed Income, or rates experience – including hands-on experience with economic analysis, Fixed Income instruments, FX markets, and direct leadership collaboration with Macro portfolio managers and senior analysts
• Experience managing cross-functional initiatives and driving change management in fast-paced trading environments
Technical Skills
• Experience architecting, integrating and scaling LLMs and AI models into production applications
• Understanding of AI agent architectures and multi-agent systems
• Familiarity with OpenAI APIs, Anthropic Claude, or similar AI services, LLM frameworks such as LangChain and LlamaIndex, and emerging AI technologies
• Expert-level proficiency in Python & SQL for data manipulation, statistical modeling and machine learning
• Familiarity with containerization (Docker) and orchestration (Kubernetes)
• Experience with cloud platforms (AWS preferred)
• Experience with vector databases and RAG systems
• Strong understanding of software engineering best practices, CI/CD, and infrastructure as code
Education:
• Master's degree in Data Science, Computer Science, Statistics, Mathematics, Economics, Finance, or equivalent work experience. MBA or PhD preferred for leadership scope
• Advanced academic training in computer science, statistics, and data science techniques (including machine learning methods) is required
• Strong preference for candidates with academic training in generative AI techniques and macroeconomic or Fixed Income analysis