Senior AI Software Engineer — T. Rowe Price Lab (NY or MD)

At T. Rowe Price, we identify and actively invest in opportunities to help people thrive in an evolving world. As a premier global asset management organization with more than 85 years of experience, we provide investment solutions and a broad range of equity, fixed income, and multi-asset capabilities to individuals, advisors, institutions, and retirement plan sponsors. We take an active, independent approach to investing, offering our dynamic perspective and meaningful partnership so our clients can feel more confident.

We believe doing the right thing for our clients and our associates is good business. With a career at the firm, you can expect opportunities to create real impact at work and in your community. You’ll enjoy resources to support your career path, as well as compensation, benefits, and flexibility to enrich your life. Here, you’ll find a collaborative culture that respects and values differences and colleagues who share a spirit of generosity.

Join us for the opportunity to grow and make a difference in ways that matter to you.

Role Summary Positions are available in our New York City office or with our AI Engineering squad in Harbor Point, Baltimore, MD. In either location, you will join a collaborative team of engineers, product owners, and business partners building high-impact AI products with leverage across the firm.

As a Senior Software Engineer on T. Rowe Price Labs’ AI Engineering team, you will independently design, build, and scale production-grade AI agents and intelligent systems that solve complex business problems. You will lead technical workstreams, incubate new AI products, experiment with emerging technologies and innovative ideas, and partner with business-aligned technology teams to enable broader adoption at scale.

This is a hands-on role for an experienced engineer with strong software fundamentals, practical AI engineering experience, and a product mindset. You will take ownership of complex and ambiguous problems, mentor other engineers, and contribute to the patterns and practices that shape AI engineering at T. Rowe Price.

Responsibilities

• Own the end-to-end design and delivery of production-grade AI agents and intelligent systems, including architecture, implementation, testing, evaluation, deployment, observability, and production support.
• Design agentic workflows using orchestration, tool integration, retrieval-based systems, structured outputs, context management, and appropriate human-in-the-loop patterns.
• Partner with product owners and business stakeholders to take control of complex or ambiguous problems, evaluate alternative approaches, and translate needs into scalable AI solutions.
• Lead technical workstreams from rapid experimentation and validation through production adoption.
• Establish evaluation and testing approaches for non-deterministic AI systems, including quality metrics, regression testing, failure analysis, and production monitoring.
• Make informed engineering trade-offs across models, prompts, context, tools, latency, cost, reliability, security, and maintainability.
• Contribute to reusable AI capabilities and shared engineering patterns that improve speed, quality, and consistency across teams.
• Lead code and design reviews, mentor less-experienced engineers, and help others solve complex technical problems.
• Own technical debt and continuously improve the quality, reliability, and maintainability of the systems you build.
• Rapidly evaluate emerging AI technologies and determine when and how they can be applied to deliver meaningful business value.
• Support the Build-Operate-Transfer model by preparing successful AI solutions for long-term ownership and scale by business-aligned technology teams.

Business Knowledge

• Work directly with business stakeholders and product owners to understand priorities, shape solution direction, and deliver measurable outcomes.
• Translate complex business needs into effective technology solutions and clearly communicate technical trade-offs.
• Balance innovation, business value, scalability, risk, fiscal responsibility, and long-term maintainability when making technical decisions.

Qualifications Required:

• BS or MS in Computer Science or a related technical field, or equivalent practical experience, with 5+ years of professional software engineering experience.
• Strong hands-on development experience in object-oriented languages such as…