AI-Enabled Software Architect & Tech Leader

McKinsey & Company

Atlanta (GA)

On-site

USD 175,500 - 180,000

Full time

14 days+

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Benefits offered by this job

World-class benefits

Competitive salary

Global team and growth opportunities

Job summary

McKinsey & Company in the United States is seeking a senior software engineer to drive architectural decisions and technical direction across a data-driven AI-enabled platform. You will design robust systems, mentor engineers, and collaborate with product managers and clients to deliver scalable, production-ready solutions.

You will work hands-on across full stack, evaluate frameworks, design APIs, and implement cloud-native patterns across AWS/Azure/GCP.

Qualifications

Undergraduate or master's degree; or equivalent experience.
5+ years of experience developing full-stack applications, writing code that is readable, testable, maintainable, and scalable.
Deep proficiency in at least two frontend or backend frameworks, with the ability to independently evaluate and select packages, define data structures, and deliver robust, scalable solutions across the full stack; hands-on experience with languages and frameworks including JavaScript/TypeScript, React, Angular, Next.js, Vue.js, Java, Spring, C#, or Node.js; SQL and NoSQL databases; cloud platforms (AWS, Azure, or GCP); and CI/CD tooling (Jenkins, Docker, CircleCI, or similar)
Demonstrated ability to design complex, secure APIs - including REST and GraphQL - with a focus on scalability and maintainability, implementing advanced features such as rate limiting, caching, and API gateways, grounded in expert knowledge of software design patterns including microservices and distributed architectures
Proficiency across two cloud providers with the ability to build complex IaC and CI/CD pipelines from scratch, implement zero downtime deployment strategies, and apply cloud-native architecture concepts to ensure scalability, reliability, and elasticity
Advanced proficiency in AI-assisted engineering, orchestrating specialized agents across parallel workstreams, building reusable agent tooling, and exercising sound technical judgment on AI safety and application boundaries
Experience architecting AI systems and ensuring engineering quality, utilizing robust LLM evaluation frameworks, guardrails, and validation methodologies to deliver reliable, production-grade AI applications
A security-first mindset, able to advocate for standards and compliance, implement authentication flows such as OAuth and OIDC, proactively identify and mitigate security issues during development, and mentor others in secure development practices; ensures quality through comprehensive testing strategies and performance optimization
Experience leading collaborative, cross-functional engineering teams and fostering a strong engineering culture
Exceptional time management to meet your responsibilities in a complex and largely autonomous work environment
Strong communication skills, both verbal and written, in English and local office language(s), with the ability to adjust your style to suit different perspectives and seniority levels

Responsibilities

Own architectural directions and technical direction for your workstream.
Design robust systems and APIs with scalable, production-ready patterns.
Mentor client and internal engineers to grow their craft and engineering practices.
Collaborate with designers, product managers, and industry experts to deliver software solutions.
Work across QuantumBlack, AI by McKinsey and QuantumBlack Labs teams to develop AI-enabled systems