Principal Forward Deployment Engineer - QuantumBlack, AI by McKinsey in London

Who You’ll Work With

Driving lasting impact and building long‑term capabilities with our clients is not easy work. You are the kind of person who thrives in a high performance/high reward culture – doing hard things, picking yourself up when you stumble, and having the resilience to try another way forward. In return for your drive, determination, and curiosity, we’ll provide the resources, mentorship, and opportunities you need to become a stronger leader faster than you ever thought possible. Your colleagues—at all levels—will invest deeply in your development, just as much as they invest in delivering exceptional results for clients.

Every day, you’ll receive apprenticeship, coaching, and exposure that will accelerate your growth in ways you won’t find anywhere else.

When you join us, you will have:

• 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.
• 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.
• 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.
• 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.

Your Impact

You’ll lead the deployment and scaling of a next‑generation AI platform designed to connect strategy to execution through advanced analytics, machine learning, and agentic systems. You’ll work directly with clients, embedded in their environments, navigating real‑world constraints that don’t surface in controlled settings. The combination of hands‑on engineering, client‑facing delivery, and direct product influence defines your role.

You will sit at the intersection of software engineering and infrastructure, bringing advanced AI capabilities into real‑world environments and ensuring they work at scale. You’ll be at the center of how these systems are deployed, adopted, and operated, helping organizations translate complex AI strategies into practical, high‑impact solutions.

You’ll take ownership of the platform delivery lifecycle, including the most demanding engagements, where environments are often non‑standard and requirements evolve quickly. You’ll lead large‑scale, multi‑workstream deployments across cloud and hybrid infrastructures in enterprise environments (e.g., AWS, Azure, GCP), guiding architectural decisions and setting direction for complex deployments across engagements.

Your work frequently involves containerized and distributed systems, including Kubernetes‑based environments, where reliability, scalability, and operational stability are critical. From validating performance and resilience to ensuring structured handovers, your work ensures systems are production‑ready and built to last.

Along the way, you’ll help shape how delivery is structured across teams, evolving tooling, automation, and delivery practices based on real‑world experience, and working hands‑on to resolve complex issues in production. The impact of your work is tangible. You’ll enable clients to run advanced AI‑driven workflows and manage intelligent systems within their existing technology ecosystems, often in regulated or multi‑region settings.

Working closely with senior technical stakeholders, you’ll help define deployment strategies, navigate complex challenges, and guide adoption through practical, experience‑led best practices. Your perspective from the field will also feed directly into product development, influencing how QuantumBlack, AI by McKinsey, technology continues to evolve.

You’ll maintain a continuous feedback loop with the product team — surfacing patterns from the field, contributing to issue resolution, and helping ensure that real‑world deployment experience shapes the platform’s evolution. Based in one of our European offices, you’ll work closely with engineers, product teams, and technical experts across the QuantumBlack, AI by McKinsey, global community.

Beyond leading deployments, you’ll collaborate with data scientists, machine learning engineers, designers, and technologists on interdisciplinary initiatives, contributing to a broader ecosystem of AI innovation. You’ll also play a key role in developing others—mentoring engineers, reviewing approaches, and helping teams raise the bar for quality and delivery.

Together, you’ll help operationalize advanced AI systems across industries, driving successful delivery, validation, and adoption in client environments. At QuantumBlack, AI by McKinsey, you’ll thrive in an unparalleled environment for growth. You’ll develop a sought‑after perspective by connecting technology and business value, work across industries, and collaborate with multidisciplinary teams to unlock the transformative potential of AI, while advancing as a technologist and leader.

Your Qualifications and Skills

• Bachelor’s or Master’s in computer science, machine learning, applied statistics, mathematics, engineering, artificial intelligence, or a related field.
• 8+ years of hands‑on experience in software, platform, or infrastructure engineering, with a track record of leading enterprise‑scale platform rollouts.
• Strong full‑stack engineering – proficiency in Python and modern web frameworks (React, NextJS or equivalent).
• Experience designing, deploying, and managing cloud‑based systems (AWS, Azure, or GCP), including containerization (Docker) and orchestration frameworks, with hands‑on experience operating and troubleshooting production systems; deep expertise in Kubernetes cluster architecture, installation, configuration, and lifecycle management at production scale.
• Experience leading complex deployments, guiding architectural decisions, and driving delivery standards across engagements in multi‑stakeholder environments.
• Strong experience with CI/CD pipelines and Infrastructure as Code (e.g., GitHub Actions, GitLab CI, Terraform, Ansible, Helm), contributing to scalable delivery automation.
• Strong understanding of data architectures and platform design, including hands‑on experience with relational databases (e.g., PostgreSQL) and familiarity with graph databases (e.g., Neo4j), alongside data pipelines and system integration patterns.
• Experience with AI‑native platform concepts, including model integration patterns, agentic architectures (tool calling, prompt orchestration, multi‑agent workflows), and data pipelines that support AI‑driven applications is a plus.
• Strong problem‑solving skills with a structured approach to debugging and resolving issues in complex, non‑standard environments, including operating and troubleshooting distributed systems in production.
• Experience with DevSecOps, infrastructure security, and networking fundamentals (e.g., IAM/SSO, RBAC, secrets management, VPNs, DNS, load balancing); experience with delivery standards, runbook development, and automation frameworks is a strong advantage.
• Familiarity with observability, monitoring, and compliance practices, and experience working in secure or regulated environments is preferred.
• Willingness to travel.
• Ability to communicate effectively in client‑facing settings, including leading technical discussions, facilitating workshops, and presenting to senior stakeholders.