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T. Rowe Price

Global asset manager offering retirement solutions

Lead AI Software Engineer

AI Application EngineeringConfirmed live in the last 24 hours
Full-time

About the Job

Requirements

  • A BS or MS in Computer Science or a related technical field, or equivalent practical experience, with 8+ years of progressive software engineering experience.
  • Extensive hands-on software engineering experience in object-oriented languages such as Python, Java, or JavaScript/TypeScript, including experience leading technical delivery across teams or major initiatives.
  • Deep hands-on experience designing and delivering AI-enabled systems, intelligent workflows, or agentic applications in production or near-production environments.
  • Strong expertise in modern AI engineering patterns such as agent orchestration, tool/function calling, retrieval-based systems, prompt and context engineering, evaluation, observability, guardrails, and failure handling.
  • Demonstrated ability to architect production AI systems and make informed trade-offs across model capability, quality, latency, cost, reliability, security, and maintainability.
  • Extensive experience architecting and delivering cloud-native solutions using AWS or equivalent, containerized microservices, APIs, and modern software delivery practices.
  • Strong understanding of evaluation and testing strategies for AI systems, including approaches for measuring and improving non-deterministic system behavior.
  • Demonstrated ability to lead engineers through complex and ambiguous technical challenges, with architecture and system-design skills.
  • Demonstrated commitment to engineering excellence through setting and upholding standards for automated testing, code reviews, observability, security, and continuous delivery.
  • Strong communication and influence skills, with the ability to shape technical direction across engineering, product, business, and senior stakeholders.
  • Demonstrated experience mentoring engineers and raising technical capability across teams.
  • Passion for staying current with the rapidly evolving AI landscape and the judgment to distinguish promising technologies from short-lived trends.

Responsibilities

  • Lead the architecture, design, development, deployment, and evolution of complex production-grade AI agents and intelligent systems.
  • Set technical direction for AI solutions, making informed trade-offs across models, orchestration patterns, retrieval, tools, data, infrastructure, latency, cost, security, reliability, and long-term maintainability.
  • Lead teams through ambiguous and technically complex AI problems, from experimentation and architecture through production adoption and scale.
  • Define and evolve engineering standards for production AI, including evaluation, testing, observability, guardrails, failure handling, security, and responsible deployment.
  • Guide the development of reusable AI capabilities and shared platform components across agent orchestration, tool use, retrieval-based systems, evaluation frameworks, observability, and guardrails.
  • Evaluate emerging models, frameworks, tools, and AI engineering approaches and provide technical direction on when and how they should be adopted.
  • Provide hands-on technical leadership and mentorship to engineers, raising the bar on architecture, engineering quality, problem solving, and execution.
  • Lead technical design and code reviews and help resolve complex engineering challenges across teams and systems.
  • Drive the Build-Operate-Transfer model by incubating new AI products, hardening them for production, and partnering with business-aligned technology teams to transition proven solutions for long-term ownership and scale.
  • Ensure AI systems achieve measurable quality, production readiness, operational observability, appropriate safety controls, and sustainable total cost of ownership.
  • Identify opportunities for shared AI platforms and abstractions, balancing reusable enterprise capabilities with product-specific requirements.
  • Identify and pursue opportunities to apply AI to accelerate workflows, improve decision-making, and create scalable business impact across the firm.
  • Engage directly with business stakeholders, product owners, senior partners, and technology leaders to understand priorities and shape solution and technical direction.
  • Translate complex and ambiguous business needs into robust AI solutions and architectures that support immediate value and broader enterprise adoption.
  • Apply product and engineering judgment to balance innovation, scalability, business value, risk, cost, security, and long-term maintainability.
  • Influence technical decisions across initiatives and communicate complex AI concepts, architectures, risks, and trade-offs effectively to technical and non-technical audiences.

Desired Qualifications

  • Experience establishing engineering standards or technical direction across multiple teams.
  • Understanding of financial markets, asset management, or financial instruments.

About the Company

T. Rowe Price

Global asset manager offering retirement solutions

T. Rowe Price provides investment management and retirement solutions to individual investors, financial intermediaries, and institutions worldwide. It manages client assets through a disciplined, research-driven investment process and offers a range of strategies and products designed for long-term value. Clients pay management fees based on assets under management, with total assets under management around $1.569 trillion as of June 30, 2024. The company differentiates itself by its global research capabilities, experienced investment teams, and broad client base, enabling tailored solutions for personal accounts, retirement plans, and institutional clients. Its goal is to help clients reach their financial objectives by growing and preserving capital over the long term through diversified investment strategies.

Company size
10,001+
Company stage
IPO
Headquarters
Baltimore, MD
Founded
1937

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