Senior Software Engineer & Tech Lead — AI & Architecture

McKinsey & Company; New York (NY); On-site; USD 175,500 - 180,000; Full time

Benefits offered by this job

Competitive salary

Comprehensive benefits package

Job summary

McKinsey & Company seeks a client-facing technologist to lead AI-enabled software engineering across full-stack systems. You will own architectural decisions, drive technical direction, and deliver scalable, production-ready solutions while mentoring engineers and shaping engineering practices.

You will work with cross-functional teams and clients, collaborating with QuantumBlack and AI by McKinsey to build robust foundations for enterprise AI.

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 decisions and set the technical direction for your workstream.
• Design robust systems and make architectural judgments on framework selection and cloud design.
• Mentor client and internal engineers to grow their craft and engineering practices.
• Collaborate with QuantumBlack, AI by McKinsey, and QuantumBlack Labs teams to develop scalable AI-enabled software.
• Help accelerate AI adoption and deliver high-value solutions for clients at scale.

Skills

Full-stack development

Frontend frameworks

Backend frameworks

API design

Cloud platforms

CI/CD tooling

AI engineering leadership

Security and compliance

Team leadership

English communication

Education

Undergraduate or Master's degree; or equivalent experience

Tools

Docker

CircleCI

Jenkins

AWS

Azure

GCP

REST

GraphQL

Job description

McKinsey & Company seeks a client-facing technologist to lead AI-enabled software engineering across full-stack systems. You will own architectural decisions, drive technical direction, and deliver scalable, production-ready solutions while mentoring engineers and shaping engineering practices.

You will work with cross-functional teams and clients, collaborating with QuantumBlack and AI by McKinsey to build robust foundations for enterprise AI.