AI Software Engineer- T. Rowe Price Labs (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 Software Engineer on T. Rowe Price Labs’ AI Engineering team, you will design, develop, and deploy AI agents and intelligent systems, helping move ideas from concept toward enterprise scale. Working in a Build-Operate-Transfer model, you will contribute to incubating new AI products, help harden them for production, and partner with business-aligned technology teams to help scale responsible AI solutions across the firm.

This is a hands-on engineering role for someone who enjoys solving technical problems, working across disciplines, and learning how modern AI products are built responsibly. You will contribute to reusable AI capabilities, help apply strong engineering standards and best practices, and collaborate with senior and lead engineers as you grow your skills and help shape the future of AI engineering at T. Rowe Price.

Responsibilities

• Design, build, test, and deploy AI agents and intelligent systems for modern cloud-based, n-tier, cloud-native architectures.
• Work closely with engineers, product owners, and business stakeholders to develop agent-driven workflows that automate complex processes and generate actionable insights.
• Contribute to product incubation efforts by helping validate ideas, build robust implementations, and prepare solutions for production adoption.
• Support the transition of proven capabilities through the Build-Operate-Transfer model, partnering with business-aligned technology teams for long-term ownership and scale.
• Contribute to reusable AI capabilities across areas such as agent orchestration, prompt engineering, tool use, retrieval-based systems, evaluation frameworks, observability, and guardrails.
• Champion engineering excellence by applying best practices in AI development, automated testing, code quality, continuous integration, and continuous delivery.
• Manage technical debt and drive ongoing improvements in AI platforms and infrastructure.
• Proactively seek opportunities to apply AI agents for increased business value and operational efficiency.

Business Knowledge

• Collaborate directly with business stakeholders and product owners to understand needs and priorities.
• Make technology decisions that support current and future business objectives and fiscal responsibility.
• Translate business requirements into effective technology solutions.

Qualifications

Required:

• BS or MS in Computer Science or a related technical field (or equivalent experience), with 2+ years of professional development experience in an object-oriented language (Java, Python, or JavaScript preferred).
• Hands-on experience with cloud-native architectures (AWS, Azure), containerized microservices, and agent frameworks.
• Exposure to or strong interest in AI-enabled systems, intelligent workflows, or agentic applications.
• Familiarity with modern AI engineering patterns such as agent orchestration, tool integration, retrieval-based systems, evaluation approaches, monitoring, or guardrails is a plus.
• Strong analytical and problem-solving abilities.
• Commitment to quality via automated testing, code reviews, and c…