Principal Engineer, Digital Identity – Risk Intelligence

We are seeking a Principal Engineer to join our Risk Intelligence / Digital Identity & Fraud (DI&F) organization. This is a senior individual contributor role responsible for leading complex technical initiatives and owning technical direction for a critical product, platform, or engineering domain. The role combines architecture, hands-on engineering, and delivery leadership, working closely with development teams, architects, product owners, and quality leads to build secure, scalable, resilient, cloud-native solutions that support fraud prevention, identity verification, and account validation services.

The successful candidate will operate at both strategic and execution depth: shaping architecture, influencing design decisions, decomposing large initiatives into executable work, mentoring engineers, improving standards and reuse, and remaining actively involved in day-to-day engineering work including design reviews, problem solving, implementation guidance, and delivery support.

Role Responsibilities & Key Accountabilities Own technical direction and engineering outcomes for a defined DI&F product, platform, or capability area, ensuring solutions align with business needs, platform strategy, and engineering standards.

Design, develop, and enhance high-performance APIs and distributed platform capabilities used for fraud prevention, identity verification, and account validation.

Provide hands-on technical leadership through solution design, architecture guidance, code review, prototyping, issue resolution, and implementation support across the software development lifecycle.

Lead the design and evolution of microservices-based distributed systems using cloud-native architecture and modern engineering practices.

Work closely with architects, product owners, and quality leads to decompose solutions into epics, lead design planning, and break initiatives into executable journeys for engineering teams.

Own delivery of critical platform capabilities, working with a high degree of autonomy while mentoring others and helping ensure timely completion of work across the team.

Improve engineering quality, resilience, performance, observability, security, and reusability through shared patterns, technical standards, and strong implementation discipline.

Drive a security-first and risk-aware engineering approach by evaluating design trade-offs, resolving blockers, and building resilience and operational readiness into systems and delivery practices.

Build and deploy containerized solutions using Docker and Kubernetes across cloud platforms such as Azure, AWS, or GCP.Ensure code quality through adherence to SOLID principles, sound design patterns, automated testing, and engineering quality tooling such as Sonar Qube and Coverity.

Use data, experimentation, customer feedback, and operational insight to validate assumptions and continuously improve systems and engineering methods.

Build strong relationships with internal and external stakeholders and communicate complex technical information clearly to both technical and non-technical audiences.

Mentor engineers and raise the bar for technical quality, delivery practices, and engineering capability across the team.

Qualifications & Experience Significant experience in software development and delivery, with demonstrated success leading complex technical work in product or platform engineering environments.

Significant experience driving AI-enabled engineering practices in complex enterprise software environments, with measurable impact on developer productivity, engineering quality, and delivery outcomes.

Demonstrated ability to identify, evaluate, and implement modern AI-assisted development approaches that improve architecture, design, coding efficiency, testing effectiveness, and operational support.

Deep hands-on expertise in .NET Core / C# or Java, with strong experience designing and delivering enterprise-grade backend systems and APIs.Strong experience with microservices, distributed systems, and cloud-native application design.

Strong understanding of software architecture, scalable system design, engineering patterns, and how to apply them effectively in enterprise solutions.

Experience with relational databases such as PostgreSQL and MySQL, including strong SQL and data modeling skills.

Experience with Docker, Kubernetes, and one or more major cloud platforms such as Azure, AWS, or GCP.Ability to guide technical design, influence architecture decisions, and mentor peers through…