Lead Software Engineer (Native Mobile AI Engineering)
T. Rowe Price
An application made for this job — a tailored resume and cover letter that speak straight to the posting.
Job summary
T. Rowe Price seeks an experienced, hands-on technology leader to shape AI-enabled software engineering across our mobile organization.
You will design, build, and scale AI-native workflows for native mobile apps, partnering with engineering, architecture, product, design, security, and platform teams to modernize mobile development practices. The role requires deep expertise in native mobile engineering, strong architectural fundamentals, and hands-on work building AI-assisted engineering
Qualifications
- Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical field.
- 8+ years of experience in software engineering, native mobile engineering, or technical leadership roles.
- Strong hands-on experience building native mobile applications for iOS and/or Android.
- Proven experience leading engineering delivery across cross-functional teams.
- Hands-on experience designing, building, or operating AI-enabled or agentic engineering workflows in real-world software development environments.
- Strong software engineering fundamentals, including architecture, APIs, testing, release processes, and modern development practices.
- Experience translating business and product requirements into technical specifications, engineering plans, and production-ready solutions.
- Experience applying AI to improve engineering systems and workflows at scale.
- Strong communication and influencing skills across engineers, architects, stakeholders, and leaders.
- Ability to operate effectively in ambiguous, fast-moving environments.
Responsibilities
- Lead technical execution across one or more native mobile domains, partnering with engineering, architecture, product, design, security, and platform stakeholders.
- Translate business and product requirements into engineering-ready technical designs, implementation plans, and scalable mobile solutions.
- Drive high-quality engineering outcomes aligned with architecture standards, platform strategy, security requirements, and release goals.
- Apply AI across the software development lifecycle to improve quality, speed, consistency, and maintainability.
- Serve as a hands-on technical leader who defines engineering patterns and contributes to implementation.
Skills
Education
Tools
Job description
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.
We are seeking an experienced, hands‑on technology leader to shape how AI‑enabled software engineering evolves across our mobile organization. This role will focus on designing, building, and scaling AI‑native engineering workflows that improve how native mobile applications are architected, developed, tested, and released. The ideal candidate brings deep expertise in native mobile engineering, strong software architecture fundamentals, and practical experience building AI‑assisted or agentic engineering workflows. This person will partner closely with engineering, architecture, product, design, security, and platform teams to modernize mobile development practices and accelerate the path from requirements and design intent to production‑ready software.
- Native mobile engineering leadership
- AI-enabled software development workflows
- Spec-driven engineering and technical design
- Agentic workflow design and orchestration
- Engineering quality, testing, and release automation
- Cross-functional technology leadership
- Lead technical execution across one or more native mobile domains, partnering with engineering, architecture, product, design, security, and platform stakeholders
- Translate business and product requirements into engineering‑ready technical designs, implementation plans, and scalable mobile solutions
- Drive high‑quality engineering outcomes aligned with architecture standards, platform strategy, security requirements, and release goals
- Apply AI across the software development lifecycle to improve quality, speed, consistency, and maintainability
- Serve as a hands‑on technical leader who defines engineering patterns and contributes to implementation
- Design, build, and operationalize AI and agentic workflows that improve:
- Technical analysis and decomposition
- Engineering specification generation
- Design‑to‑engineering translation
- Code generation and review support
- Test case generation and validation
- Release readiness and deployment workflows
- Documentation and engineering knowledge capture
- Develop reusable engineering assets, including:
- Prompt and context libraries
- Agent instructions and workflow templates
- Structured technical specification standards
- Validation frameworks for AI‑assisted outputs
- Reusable native mobile implementation and testing patterns
- Establish mechanisms for:
- Human‑in‑the‑loop review and engineering quality control
- Workflow evaluation and continuous improvement
- Performance tuning and optimization of AI‑enabled systems
- Traceability across AI‑generated outputs, engineering decisions, and release artifacts
- Improve how teams move from requirements and design artifacts to engineering‑ready specifications and implementation
- Establish and scale spec‑driven engineering practices for iOS and Android development
- Integrate tools such as GitHub, CI/CD pipelines, Confluence, Figma, Jira, and AI platforms into repeatable development workflows
- Strengthen design‑to‑code handoffs and improve engineering readiness across the delivery lifecycle
- Advance automation across coding, testing, validation, and release processes
- Improve software quality, observability, telemetry, and release confidence through AI‑enabled engineering practices
- Identify opportunities to fundamentally improve how engineering work is performed through AI, not just accelerate isolated tasks
- Pilot, evaluate, and scale AI‑enabled engineering capabilities across native mobile teams
- Assess emerging AI tools, coding assistants, frameworks, and orchestration patterns for enterprise use
- Help define best practices for safe, scalable, and effective AI adoption in software engineering
- Contribute to the broader engineering strategy for AI‑assisted development, workflow modernization, and technical enablement
- Collaborate closely with mobile engineers, architects, platform teams, product managers, designers, and business stakeholders
- Communicate complex technical concepts clearly to technical and non‑technical audiences
- Align engineering execution with business priorities, technical strategy, risk controls, and user experience goals
- Influence engineering standards and ways of working through technical depth, credibility, and hands‑on leadership
- Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience
- 8+ years of experience in software engineering, native mobile engineering, or technical leadership roles
- Strong hands‑on experience building native mobile applications for iOS and/or Android
- Proven experience leading engineering delivery across cross‑functional teams
- Hands‑on experience designing, building, or operating AI‑enabled or agentic engineering workflows in real‑world software development environments
- Strong software engineering fundamentals, including architecture, APIs, testing, release processes, and modern development practices
- Experience translating business and product requirements into technical specifications, engineering plans, and production‑ready solutions
- Experience applying AI to improve engineering systems and workflows at scale
- Strong communication and influencing skills across engineers, architects, stakeholders, and leaders
- Ability to operate effectively in ambiguous, fast‑moving environments
- Experience designing or scaling agentic workflows, prompt libraries, or context repositories for engineering teams
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