AI-Native Mobile Engineering Lead & Workflow Architect

T. Rowe Price

Owings Mills (MD)

On-site

USD 170,000 - 240,000

Full time

4 days ago

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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.