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Role Summary

This is a rare opportunity to sit at the frontier of investment and artificial intelligence, building systems that redefine what's possible in active management. You will help pioneer a new generation of AI-powered investment capabilities that expand human insight, accelerate alpha generation, and shape the future of how T. Rowe Price delivers value to clients globally.

The Investment AI Solutions Analyst plays a pivotal role in realizing that future. This role combines deep investment knowledge with leading technical expertise in AI systems design to create, deploy, and operationalize agentic AI. These agents will enhance every facet of the investment process, from research discovery and portfolio construction to risk analysis and client engagement. Working alongside experienced analysts and portfolio managers, this role will help deliver innovative AI insights that inform better investment decisions. This is an opportunity to be part of a team deeply engaged in pioneering AI research and modern quantitative approaches, collaborating directly with our fundamental research platform on initiatives that help shape the future of the firm's investment strategies.

Guiding teams of investors, AI engineers, technologists, and architects, you will enhance the capabilities of investors and shape the next era of investment management where autonomous systems reason, plan, and act in collaboration with human investors. These systems will not only drive superior investment outcomes but also uncover new opportunities and redefine how institutional investors generate insight at scale.

Responsibilities

Build Strategic Relationships with Stakeholders:

• Develop and maintain strong, consultative relationships with fundamental analysts and portfolio managers (PMs). Understand each stakeholder's investment framework, objectives, and decision-making approach.
• Serve as a highly regarded subject matter expert in AI. Identify opportunities where AI can add meaningful value to fundamental investors.
• Define the product roadmap, assess feasibility, and establish accountability in close partnership with stakeholders.

Architect the Next Generation of Investment Intelligence:

• Design and deliver agentic architectures that integrate LLMs, quantitative models, enterprise data pipelines, and real-time reasoning systems.
• Deploy and drive adoption of agents that understand financial context, retrieve relevant knowledge, and generate research-grade outputs that enhance the work of investors.
• Implement robust guardrails, compliance checks, and observability frameworks to ensure agents operate reliably in production investment environments.
• Continuously evaluate and integrate emerging frameworks in multi-agent coordination, retrieval-augmented generation (RAG), and prompt design.

Fuse AI and Research:

• Partner with fundamental and quantitative investors to identify high-value opportunities for AI-enabled automation and augmentation.
• Translate complex investment problems into structured AI workflows that generate measurable alpha and enhance decision velocity.
• Push relevant research proactively to analysts and PMs, supplementing their ongoing decision-making process.
• Present research and recommendations confidently in meetings and formal presentations to the investment team.

Collaborate, Lead, and Transform:

• Work across Investment, Data Science, and Technology teams to deliver AI-native capabilities that modernize T. Rowe Price's investment platform.
• Lead workflow transformations that translate complex processes into intelligent agentic solutions.
• Continuously develop investment workflow prototypes to test the feasibility of fully autonomous, self-improving systems.
• Help institutionalize best practices for prompt engineering, orchestration, and responsible AI across the investment organization.

Success Measures:

• Strength and breadth of relationships with key stakeholders (Analysts, PMs, Investments leadership).
• Measurable productivity gains from agentic workflows through increased awareness and utilization by fundamental investors.
• Measurable improvement to investment results and incremental revenue generation.
• Ideation, design, and execution of next-generation investment management capabilities.

Qualifications

Required:

• B.S. in a quantitative discipline (Computer Science, Applied Mathematics, Statistics, or related field).
• Expert-level proficiency in programming languages (R or Python) and experience applying these to agentic AI systems (e.g., LangChain, AutoGen, CrewAI, Semantic Kernel, or LangGraph).
• Exceptional skills in prompt engineering, assessing use cases for agentic feasibility, and converting complex workflows into logical, step-by-step tasks.
• Deep expertise in data modeling, processing, integration, and analytics, with demonstrable proficiency in enterprise data platforms (e.g., Snowflake, Databricks, BigQuery).
• Strong track record of innovation and problem-solving to find creative technical solutions to new and unforeseen business problems.
• Ability to travel to support deployments across the global organization.
• Strong communication skills, with the ability to synthesize complex AI and investment concepts for diverse audiences.
• 5+ years' experience with financial modeling, portfolio construction, trading, or investment management workflows.

Preferred:

• M.S. or Ph.D. in a quantitative discipline.
• Leadership experience driving technology and investment teams.
• 3+ years developing agentic AI systems (e.g., LangChain, AutoGen, CrewAI, Semantic Kernel, or LangGraph).
• 10+ years' experience with financial modeling, portfolio construction, trading, or investment management workflows.
• Experience with advanced retrieval-augmented generation and multi-agent systems.
• Certifications such as:
  • Databricks Certified Generative AI Engineer Associate
  • SnowPro Specialty: Gen AI
  • AWS Certified Machine Learning Engineer - Associate
  • AWS Certified Machine Learning - Specialty
• CFA charterholder or active candidate.

FINRA Requirements

FINRA licenses are not required and will not be supported for this role.

Work Flexibility

This role is eligible for hybrid work, with up to one day per week from home.