Senior AI Software Engineer — T. Rowe Price Labs
About The Position
T. Rowe Price Labs is hiring a Senior Software Engineer for its AI Engineering team, with positions available in the New York City office or at Harbor Point in Baltimore, Maryland. The role joins engineers, product owners, and business partners to build high-impact AI products for use across the firm. The engineer will independently design, build, and scale production-grade AI agents and intelligent systems that address complex business problems. The role includes leading technical workstreams, incubating AI products, experimenting with emerging technologies, and partnering with business-aligned technology teams to support adoption at scale. This is a hands-on position for an experienced engineer with strong software fundamentals, practical AI engineering experience, and a product mindset. The successful candidate will own complex and ambiguous problems, mentor engineers, and contribute to the practices and patterns guiding AI engineering at T. Rowe Price. The role works directly with business stakeholders and product owners to understand priorities, shape solution direction, and deliver measurable outcomes. It is eligible for hybrid work, with up to three days per week from home. FINRA licenses are not required and will not be supported for this role.
Requirements
- BS or MS in Computer Science or a related technical field, or equivalent practical experience.
- At least 5 years of professional software engineering experience.
- Strong hands-on development experience in object-oriented languages such as Python, Java, or JavaScript/TypeScript.
- Hands-on experience building AI-enabled applications, intelligent workflows, or agentic systems using modern LLMs and AI development frameworks.
- Practical experience with AI engineering patterns such as agent orchestration, tool/function calling, retrieval-based systems, prompt and context engineering, structured outputs, evaluation, observability, or guardrails.
- Experience taking AI-enabled systems beyond prototypes toward production, including testing, monitoring, reliability, security, and operational considerations.
- Strong experience with cloud-native architectures, containerized microservices, APIs, and modern software delivery practices.
- Strong analytical, problem-solving, software design, and debugging skills.
- Commitment to engineering quality through automated testing, code reviews, observability, and continuous delivery.
- Ability to independently own complex technical problems and clearly communicate designs, decisions, and trade-offs.
- Product mindset, strong learning agility, and interest in keeping current with the evolving AI engineering landscape.
Nice To Haves
- Experience mentoring engineers or leading technical workstreams.
- Understanding of financial markets, asset management, or financial instruments.
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 address complex or ambiguous problems, evaluate 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 engineering trade-offs across models, prompts, context, tools, latency, cost, reliability, security, and maintainability.
- Contribute 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 systems.
- Evaluate emerging AI technologies and determine how they can deliver meaningful business value.
- Prepare successful AI solutions for long-term ownership and scale by business-aligned technology teams through the Build-Operate-Transfer model.
- Understand business priorities, shape solution direction, deliver measurable outcomes, and communicate technical trade-offs.
- Balance innovation, business value, scalability, risk, fiscal responsibility, and long-term maintainability in technical decisions.
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
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What This Job Offers
Job Type
Full-time
Career Level
Senior
