Job Description

About the Role

As a

Staff Software Engineer and Tech Lead Manager (TLM)

on the

Security Risk & Compliance Automation

team, you will combine technical leadership with people management. You'll architect and deliver backend systems at scale that power Uber's enterprise GRC automation platform, while also growing and mentoring a team of engineers.



This dual role is for hands-on leaders who thrive at the intersection of system design, mentorship, and cross-functional alignment.

What the Candidate Will Need / Bonus Points

- What the Candidate Will Do -

Design and Review Architecture

: Lead the design of large-scale backend services for Uber's GRC automation platform; review and guide system design proposals from team members to ensure scalability, reliability, and compliance.

Hands-On Coding

: Contribute directly to backend services in Go, Java, or Python - staying close to the codebase while delegating appropriately.

Team Leadership & Mentorship

: Provide regular feedback, career development coaching, and technical mentorship to a small team of engineers, ensuring high productivity and growth.

Cross-Functional Collaboration

: Partner with Product, Security, Compliance, and Platform Engineering teams to align roadmaps and deliver solutions that support global risk and compliance goals.

Operational Excellence

: Monitor key service metrics, lead incident response reviews, and drive continuous improvement in availability, performance, and quality.

Project Ownership

: Ensure projects are executed with clear timelines, unblock dependencies, and balance short-term deliverables with long-term system health.

Scaling People & Systems

: Model the balance between being a strong individual contributor and a people leader - raising the technical bar while building a cohesive, inclusive engineering culture.


- Basic Qualifications -

9+ years

of experience building and operating large-scale distributed systems. Proven experience setting technical direction and leading a team through the full lifecycle of a new product or platform . Strong knowledge of backend technologies (e.g., Go, Java, Python) and cloud-native infrastructure. Expertise in system design, distributed architectures, performance tuning, and API development. Experience leading the design, development, and delivery of systems that support AI/ML applications in production (e.g., model serving platforms, feature engineering pipelines, large-scale data processing). Ability to make sound engineering/business tradeoffs across multiple priorities.


- Preferred Qualifications -

Experience in Staff+ or TLM roles in high-scale environments. Strong written and verbal communication skills with the ability to influence engineering direction across teams. Experience defining a multi-year technical vision and strategy for an engineering team, particularly in an ambiguous or greenfield domain. Deep understanding of how modern AI techniques, including NLP/LLMs, can be applied to solve complex problems in the Governance, Risk, and Compliance space. Working knowledge of security, compliance, or privacy frameworks is a plus. Leadership and Mentorship: Ability to mentor junior engineers and actively contribute to team development and growth. * Passion for building cohesive, inclusive teams and scaling engineering culture.