VP, Investment AI Engineer
About the position The Investment AI Engineer is a senior, execution-focused individual in the Investment team, working alongside quantitative researchers and portfolio managers to design, build, and operate agentic solutions that accelerate the investment process. The role partners with Technology to evolve production-grade, enterprise AI capabilities, while remaining focused on building investment-specific skills, sub-agents, and workflows that enable safe, repeatable automation within research and portfolio workflows. This position reflects a broader shift toward instruction-driven development and human-in-the-loop agentic systems that augment investment teams while preserving judgment, rigor, and accountability. Acadian supports a hybrid work environment; employees are on-site in the Boston office 3 days a week.
Responsibilities
- Deliver reusable skills that encode investment workflows, conventions, and institutional knowledge for use across the Investment team.
- Implement safe automation practices, including human-in-the-loop review, testing, and controlled execution of agentic workflows.
- Design, build, and operate investment-facing AI agents, skills, and workflows that automate repeatable research and portfolio tasks.
- Define and maintain guardrails around cost, data access, agent scope, and commit size to ensure reliable and responsible usage.
- Partner directly with quantitative researchers and portfolio managers to prototype, refine, and productionize AI-enabled workflows.
- Measure and improve the outcomes of AI-enabled workflows, including adoption, quality, and time-to-value.
- Identify opportunities where agentic workflows can meaningfully improve investment productivity and decision support.
- Establish and reinforce review norms for agent-generated changes, ensuring clarity of intent, auditability, and accountability.
- Contribute to defining best practices for instruction-driven development and agentic workflows within the Investment team.
- Serve as a point of continuity between evolving AI capabilities and practical investment use cases, helping the team adapt as tools mature.
Requirements
- Bachelor’s degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience.
- Significant experience as a software or AI engineer delivering production-grade systems, with a focus on execution rather than research prototypes.
- Demonstrated experience building and operating AI- or LLM-enabled tooling, automation, or agentic workflows in real-world environments.
- Strong proficiency in Python, AWS, and modern development practices, including testing, version control, and CI/CD.
- Experience translating complex domain intent (e.g., research or investment workflows) into clear specifications and reliable software artifacts.
- Ability to reason clearly about tradeoffs involving quality, cost, speed, and risk, and to apply those tradeoffs in day-to-day execution.
- Experience working closely with quantitative researchers, portfolio managers, or similarly sophisticated domain experts.
- Demonstrated ability to operate effectively in collaborative, fast-moving environments where tools, patterns, and best practices are evolving.
Benefits
- In addition to base pay, this position may be eligible for discretionary incentive compensation and includes participation in Acadian’s comprehensive benefits program, which includes health, retirement, and wellness offerings.
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