You will collaborate with other platform engineering teams, designers, and product experts across the globe to build secure, scalable platforms that support McKinsey’s client service, practices, and domains in delivering distinctive, tech-enabled impact.
As a Principal Software Engineer, you will lead the design and development of scalable, secure, and high-performing solutions that power McKinsey’s global technology ecosystem. You will architect, develop, and integrate systems that underpin Platform McKinsey’s mission — providing a unified foundation for analytics, software engineering, and client delivery. In addition to building and maintaining these platforms, you’ll guide engineering excellence, mentor senior engineers, and drive architectural decisions that shape the future of McKinsey’s technology ecosystem. You will also apply and champion AI-assisted development practices by leveraging AI tools for coding, testing, and documentation to enhance productivity, code quality, and engineering efficiency across teams.
Your responsibilities include, but are not limited
to:
Leading the design, architecture, and development of
distributed systems and cloud-native platforms;
Driving architectural decision-making, documenting
designs in Architecture Decision Records (ADRs), and ensuring alignment with
firm-wide engineering standards;
Overseeing the end-to-end product lifecycle, from concept
and design through implementation, testing, deployment, and operations;
Writing, reviewing, and maintaining high-quality, secure,
and maintainable code across back-end and front-end systems;
Mentoring and coaching engineers across teams, fostering
technical excellence and continuous learning;
Partnering with product managers and designers to
translate business requirements into robust technical solutions;
Contributing to and evolving shared developer platforms
and tooling that improve efficiency and enable innovation firmwide;
Collaborating cross-functionally with engineering
leadership across the Tech Ecosystem to ensure consistent architectural
patterns, best practices, and governance;
Supporting users, troubleshooting applications, and
continuously improving reliability, observability, and scalability of core
systems;