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
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
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
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

Requirements

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.

Benefits

Competitive compensation
Annual bonus eligibility
A generous retirement plan
Hybrid work schedule
Health and wellness benefits, including online therapy
Paid time off for vacation, illness, medical appointments, and volunteering days
Family care resources, including fertility and adoption benefits

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard skills

RPythonagentic AI systemsprompt engineeringdata modelingdata processingdata integrationdata analyticsfinancial modelingportfolio construction

Soft skills

communication skillsproblem-solvinginnovationcollaborationleadershippresentation skillsrelationship buildingconsultative skillssynthesis of complex conceptsadaptability