Staff Software Engineer - Identity and Verifications Team

At LinkedIn, our approach to flexible work is centered on trust and optimized for culture, connection, clarity, and the evolving needs of our business. The work location of this role is hybrid, meaning it will be performed both from home and from a LinkedIn office on select days, as determined by the business needs of the team.

Team Description:

LinkedIn’s Trust Verifications team is building the identity and trust infrastructure that helps make LinkedIn a safer and more authentic professional network.

Our systems power verification experiences and trusted identity signals across LinkedIn, supporting use cases spanning member identity, employment and workplace verification, trusted hiring experiences, and portable professional identity across partner ecosystems.

The technical problems we solve sit at the intersection of digital identity, trust and abuse prevention, distributed systems, high-scale serving infrastructure, partner APIs, and member-facing product experiences. We build platforms that integrate with multiple identity providers and verification methods, process signals across real-time, nearline, and offline systems, and make trustworthy verification data available safely and reliably across LinkedIn products and external integrations.

About the role:

We are looking for a Staff Software Engineer to serve as a system architect and technical anchor for our Trust and Verifications organization.

This role sits at the intersection of large-scale distributed systems, identity and trust infrastructure, product architecture, reliability, data, and business strategy. You will partner closely with engineering and product leadership to translate ambiguous product and business opportunities into scalable technical strategies and durable platform capabilities.

You will be expected to see beyond an individual service or project: understand how systems interact across organizational boundaries, identify where common abstractions and platform investments are needed, and make architectural decisions that allow the organization to move faster over time.

The ideal candidate combines deep backend and distributed-systems expertise with strong product judgment. You can move fluidly between business goals, product requirements, APIs, data models, storage systems, distributed workflows, operational characteristics, and measurable outcomes.

You bring a high technical bar, meticulous attention to detail, strong ownership, intellectual curiosity, and a solutions-oriented mindset. You proactively identify risks, failure modes, and edge cases; communicate clearly when trade-offs exist; and help teams converge on pragmatic architectures that are scalable, reliable, secure, and evolvable.

Responsibilities

• Own Technical Strategy & Architecture: Define the technical strategy and architecture for a major product or platform area. Make long-term architectural decisions around system boundaries, APIs, data models, modularity, scalability, extensibility, security, and reliability.

• Translate Product Strategy into Systems: Work closely with product and engineering leadership to understand business goals and translate them into scalable technical capabilities. Recognize when an individual product requirement should become a reusable platform primitive rather than a one-off implementation.

• Design Large-Scale Distributed Systems: Architect complex distributed systems spanning synchronous APIs, asynchronous workflows, messaging and event-driven architectures, caching, relational and non-relational storage, and distributed state management.

• Build for Trust & Integrity: Design systems where correctness, data integrity, security, privacy, and abuse resistance are first-class architectural considerations. Think deeply about state transitions, data provenance, consistency, authorization, failure handling, and edge cases.

• Design for Reliability & Operational Excellence: Build systems that are observable, resilient, recoverable, and easy to operate. Proactively identify failure modes, capacity risks, dependency failures, data consistency issues, and operational edge cases before they become production incidents.

• Connect Architecture to Metrics: Define the engineering, product, and operational metrics required to understand whether a system is succeeding. Ensure architectures include the telemetry and observability needed to measure reliability, performance, adoption, conversion, quality, and business impact.

• Navigate Ambiguity: Take loosely defined or cross-cutting problems and create clarity. Ask the questions that expose hidden assumptions, identify technical and product trade-offs, and help teams converge on a clear strategy.

• Lead Across Organizational Boundaries & Raise the Engineering Bar: Set a high standard for system design, implementation quality, testing, code review, observability, and operational readiness. Identify systemic engineering weaknesses and drive investments that improve the organization as a whole.

• Remain Hands-On: Stay sufficiently close to implementation to validate architecture through code, prototypes, design reviews, debugging, and critical-path development.

• Multiply Other Engineers: Mentor senior engineers, create clear technical ownership boundaries, lead design and RFC reviews, and help other engineers develop stronger system-design and technical-leadership skills.