Position Overview:

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. Key to success in this role is the ability to translate abstract investment and research intent into clear, achievable specifications and high‑quality merge requests that integrate cleanly into existing production systems.

Acadian supports a hybrid work environment; employees are on-site in the Boston office 3 days a week.

What You’ll Do:

• 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.
• Translate complex, often ambiguous investment and research requirements into clear technical specifications, well-scoped tasks, and reviewable merge requests.
• Embed within existing investment teams, working closely with team leads and domain experts to translate investment intent into concrete, production‑ready agentic workflows and software changes.
• 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.

We’re Looking for Teammates With:

• 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.
• Baseline understanding of systematic or quantitative investment processes, or demonstrated ability to quickly develop intuition for how investment research translates into live portfolio decisions.
• Demonstrated judgment in distinguishing technically impressive solutions from those that are practically useful, robust, and aligned with the needs of a systematic investment organization.

The base salary range for this role is $225,000 – $275,000 per year. Actual compensation will be determined based on a candidate’s skills, qualifications, and relevant experience. 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.

Position Overview:

We are seeking a Principal Quant Engineer to work in close collaboration with Research, Portfolio Management, and Data teams to design and implement scalable, production-grade platforms that support Acadian’s quantitative research and investment processes.

This role focuses on building quant tooling that enables researchers to efficiently develop, evaluate, and deploy quantitative models across investment processes including alpha, risk, transaction cost analysis, attribution, etc. The emphasis is on creating infrastructure that makes quantitative research repeatable, observable, and production-ready at scale.

Acadian supports a hybrid work environment; employees are on-site in the Boston office 3 days a week.

What You’ll Do:

• Design and implement quant tooling that supports signal construction and evaluation workflows, powering production portfolios across global asset universes.
• Work closely with quantitative researchers to ensure research infrastructure continues to evolve in step with their needs, enabling efficient experimentation and reliable alpha generation.
• Lead the AI centric development and evolution of core platform capabilities that support signal computation, data access, workflow orchestration, and distributed execution for both quantitative signals and machine learning-based techniques, including deep learning workflows built with PyTorch.
• Ensure platform flexibility while maintaining integration with downstream processes for portfolio construction, portfolio management, marketing, client reporting, etc
• Incorporate machine learning and AI techniques into signal construction, parameter estimation, and efficacy evaluation workflows where they improve forecast quality and research productivity, including hyper‑parameter optimization using frameworks such as Optuna or similar.
• Provide architectural leadership to improve robustness, transparency, scalability, and performance of data- and compute-intensive research and production workflows.
• Collaborate with data and platform teams to streamline access to market data, alternative datasets, and compute resources, reducing friction in the research “inner loop” of signal development, backtesting, and validation.
• Contribute to the end‑to‑end machine learning lifecycle capabilities, including experiment tracking, model management, embedding and graph visualization, and deployment, drawing on tools and concepts such as MLflow.

We’re Looking for Teammates With:

• Bachelor’s degree or higher in Computer Science, Engineering, Applied Mathematics, or a related quantitative field.
• 7+ years of experience in software engineering, with significant hands-on work supporting quantitative research, signal development, or systematic investing in production environments.
• Demonstrated experience building and operating quantitative platforms that support signal modeling, evaluation, and deployment at scale.
• Strong proficiency in Python and modern data processing and numerical computing tools (e.g., Polars).
• Familiarity with machine learning and AI-assisted development techniques, including the use of AI or agentic coding tools (e.g. Claude Code) to improve research and engineering productivity.
• Solid understanding of system design concepts.
• Demonstrated ability to deliver robust, transparent, and performant systems.
• Strong attention to detail and a commitment to producing accurate, reliable, and well-engineered solutions.
• Creativity and enthusiasm for solving complex problems.
• Strong work ethic and a roll-up-your-sleeves mindset, with the ability to operate effectively in a hands-on, collaborative environment.

The base salary range for this role is $185,000 – $225,000 per year. Actual compensation will be determined based on a candidate’s skills, qualifications, and relevant experience. 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.