As a Senior Software Engineer on the Contract AI product team, you will be a strong individual contributor building features, improving platform quality, and hardening the system for scale across multiple concurrent client deployments.

You will work across the stack — from AI-powered extraction pipelines through to the analytics dashboard — and you will bring genuine GenAI engineering depth, not just familiarity.

Contract AI is McKinsey's enterprise-grade platform for automated contract compliance — using Generative AI and rule-based logic to extract, compare, and evaluate contracts and invoices at scale. Deployed into client Azure cloud environments, the platform helps global enterprises identify and recover pricing leakage across large procurement portfolios. The engineering team builds and maintains the full stack: extraction pipelines, compliance evaluation logic, data ingestion workflows, and an analyst-facing dashboard.

You will: develop and refine the AI pipeline that processes raw contracts and invoices — prompt engineering for document extraction, structured output parsing, clause normalization, and confidence scoring; translate business rules into deterministic evaluator code (Python/C#); build and maintain the library of compliance cases that power the platform's leakage detection; write production Python and C#/.NET backend code; develop TypeScript/React components in the analyst-facing dashboard; build and maintain data ingestion pipelines using Azure Data Factory.

You will also implement agentic workflows using LangGraph, Semantic Kernel, or equivalent frameworks for multi-step contract reasoning tasks; stay current with the fast-moving agentic AI landscape and bring relevant innovations into the platform; write comprehensive tests (unit, integration, end-to-end); participate actively in code reviews; instrument services with structured logging and observability tooling; configure and tune the platform for new client data schemas and pricing structures; debug and resolve issues in cloud-hosted deployment environments; participate in technical design discussions; mentor junior engineers; identify and propose improvements to engineering practices.

• Continuous learning: Our learning and apprenticeship culture, backed by structured programs, is all about helping you grow while creating an environment where feedback is clear, actionable, and focused on your development. The real magic happens when you take the input from others to heart and embrace the fast-paced learning experience, owning your journey.
• A voice that matters: From day one, we value your ideas and contributions. You’ll make a tangible impact by offering innovative ideas and practical solutions, all while upholding our unwavering commitment to ethics and integrity. We not only encourage diverse perspectives, but they are critical in driving us toward the best possible outcomes.
• Global community: With colleagues across 65+ countries and over 100 different nationalities, our firm’s diversity fuels creativity and helps us come up with the best solutions for our clients. Plus, you’ll have the opportunity to learn from exceptional colleagues with diverse backgrounds and experiences.
• World-class benefits: On top of a competitive salary (based on your location, experience, and skills), we provide a comprehensive benefits package to enable holistic well-being for you and your family.

5+ years of software engineering experience delivering production systems.

Strong Python — application development, type-checking, async patterns, testing (pytest) is required

Proficiency in C#/.NET — .NET Core/8, REST APIs, object-oriented design are required

Recent, hands-on experience integrating Generative AI into production software — Azure OpenAI, LangChain, Semantic Kernel, RAG pipelines, or structured extraction. This experience must be production use, not prototype or side-project

Demonstrated familiarity with agentic AI frameworks (LangGraph, AutoGen, CrewAI, or equivalents)

Experience with Azure cloud services: AKS, Azure Functions, CosmosDB, Postgres, Azure DevOps

Experience with TypeScript/React in production

Strong SQL skills: schema design, query optimization, Postgres preferred

Engineering discipline: test-driven development, CI/CD pipelines, code reviews, containerization (Docker/Kubernetes)

Experience with Azure Data Factory or equivalent ETL pipeline tooling

Exposure to vision LLMs and document understanding (PDF/DOCX extraction at scale)

Familiarity with procurement, contract management, or invoice processing domains