At a Glance
- Tasks: Deploy and scale next-gen AI platforms, bridging software engineering and infrastructure.
- Company: Join QuantumBlack, AI by McKinsey, a leader in AI innovation.
- Benefits: Competitive salary, comprehensive benefits, and a focus on holistic well-being.
- Other info: Dynamic global community with opportunities for mentorship and rapid career growth.
- Why this job: Make a real impact with cutting-edge AI technology in a collaborative environment.
- Qualifications: 4+ years in software/platform engineering, strong Python skills, and cloud experience.
The predicted salary is between 70000 - 90000 £ per year.
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. 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.
Your Impact
You’ll deploy and scale a next‑generation AI platform designed to connect strategy to execution through advanced analytics, machine learning, and agentic systems. 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 play a key role in how these systems are deployed, adopted, and operated, enabling organizations to translate complex AI strategies into practical, high‑impact solutions.
You’ll own the platform delivery lifecycle, bridging product engineering and client environments. Responsibilities include deploying and configuring production‑grade systems across cloud and hybrid infrastructures (e.g., AWS, Azure, GCP), validating performance and stability, and ensuring structured handovers for long‑term success. Work often involves containerized and distributed systems, including Kubernetes‑based environments, where reliability and operational stability are critical. You’ll troubleshoot issues end‑to‑end and ensure platforms are fully production‑ready, while also contributing to deployment tooling, automation, and product feedback loops to improve platform reliability and delivery.
The impact of your work is tangible. You’ll enable clients to run AI‑driven workflows and manage intelligent systems within their existing technology ecosystems. Working closely with technical stakeholders, you’ll ensure environment readiness, resolve deployment challenges, and guide adoption through practical best‑practices. Your experience from the field will also contribute to feedback loops between deployments and product development, supporting the continuous evolution of QuantumBlack, AI by McKinsey technology.
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 platform deployments, you’ll collaborate with data scientists, machine learning engineers, designers, and technologists on interdisciplinary initiatives, contributing to a broader ecosystem of AI innovation. Together, you’ll help operationalize advanced AI systems across industries, driving successful delivery, validation, and adoption in client environments. You’ll also contribute to team knowledge‑sharing — documenting patterns, refining delivery practices, and supporting colleagues across engagements.
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, Master’s in computer science, machine learning, applied statistics, mathematics, engineering, artificial intelligence, or a related field
- 4+ years of hands‑on experience as a Software or Platform Engineer, with exposure to enterprise platform deployments
- Strong engineering fundamentals with proficiency in Python and familiarity with modern full‑stack development (e.g., 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 with CI/CD pipelines and Infrastructure as Code (e.g., GitHub Actions, GitLab CI, Terraform, Ansible, Helm)
- Strong understanding of data architectures and platform design, including relational and graph databases (e.g., PostgreSQL, Neo4j), data pipelines, and system integration patterns across structured and unstructured data
- Familiarity with AI platform concepts, including model integration patterns, agentic workflows, and how AI‑driven applications interact with underlying data and infrastructure is a plus
- Strong problem‑solving skills with a structured approach to debugging and resolving issues in complex, non‑standard environments
- Experience with DevSecOps and infrastructure security practices (e.g., IAM/SSO, RBAC, secrets management, encryption) is a plus
- Experience with deployment standards, runbook development, and automation frameworks is a strong advantage
- Familiarity with observability, monitoring, and compliance tooling (e.g., Prometheus, Grafana, ELK) and experience working in secure or regulated environments is a plus.
- Willingness to travel
- Ability to communicate effectively with technical and non‑technical stakeholders in client‑facing settings, including delivering walkthroughs, documentation, and training
Senior Forward Deployed Engineer - QuantumBlack, AI by McKinsey in London employer: QuantumBlack, AI by McKinsey
At QuantumBlack, AI by McKinsey, we pride ourselves on fostering a collaborative and innovative work culture that empowers our employees to push the boundaries of technology. With a focus on professional growth, we offer extensive training and development opportunities, ensuring that our team members thrive in their careers while working on impactful projects in vibrant cities like London and Madrid. Join us to be part of a diverse global team dedicated to solving complex engineering challenges with cutting-edge AI solutions.
Contact Details:
QuantumBlack, AI by McKinsey Recruitment Team
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We think this is how you could land Senior Forward Deployed Engineer - QuantumBlack, AI by McKinsey in London
✨Join Local Tech Meetups
Get out there and mingle with fellow developers by joining local tech meetups. It’s a fantastic way to meet people who might be working at QuantumBlack, AI by McKinsey or know someone who does. Plus, you can pick up some trendy tech skills and trends while you're at it!
✨Contribute to Open Source Projects
Show off your coding chops by jumping into open-source projects. Not only does this give you practical experience, but it also gets you noticed in the dev community. You'll create a killer portfolio that speaks volumes about your skills to QuantumBlack, AI by McKinsey.
✨Tap into Online Developer Communities
Don’t underestimate the power of online developer communities like GitHub, Stack Overflow, and even Reddit. Participate in discussions, share your projects, and build your visibility. We can often find opportunities through these channels that can lead to a full-time gig at companies like QuantumBlack, AI by McKinsey.
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We think you need these skills to ace Senior Forward Deployed Engineer - QuantumBlack, AI by McKinsey in London
Some tips for your application 🫡
Show off your coding skills:When applying for a software engineering role, it's super important to showcase your coding skills. Make sure your CV includes your tech stack, any relevant programming languages you’re comfortable with, and examples of projects you've worked on. If you have a GitHub profile, link it up! We love to see code in action.
Tailor your portfolio:For a full-time role, we’d expect to see some solid examples of your work in your portfolio. Make sure to include at least two or three projects that highlight your problem-solving skills and your ability to work with different technologies. Focus on the projects that are most relevant to the position at QuantumBlack, AI by McKinsey.
Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at QuantumBlack, AI by McKinsey and how your skills align with the role. Show us your passion for software development. We dig enthusiastic candidates who understand the value of collaboration and continuous learning!
Be clear and concise:When it comes to writing your CV and cover letter, clarity is key. Avoid jargon that could confuse us and stick to simple, direct language. Highlight your achievements with quantifiable results where possible, and keep everything easy to read. A well-organised application goes a long way!
How to prepare for a job interview at QuantumBlack, AI by McKinsey
✨Brush Up on Your Coding Skills
For a full-time software engineering role, it's crucial that we stay sharp with our coding abilities. Expect technical questions that might involve solving problems on the spot or discussing algorithms. Practise on platforms like LeetCode or HackerRank to get comfortable with the types of questions that often come up.
✨Know Your Tools and Frameworks
Make sure we’re well-acquainted with the tools and technologies listed in the job description. Familiarise ourselves with any specific frameworks or programming languages mentioned. If QuantumBlack, AI by McKinsey uses React or Node.js, for instance, be ready to discuss how we’ve used them in previous projects or coursework.
✨Showcase Your Projects
Bring along a portfolio that highlights our best work. This could be code samples, GitHub repositories, or any side projects we’ve built. Make sure we can talk through our thought process for each project, especially the challenges we faced and how we solved them—this shows our problem-solving skills in action.
✨Prepare for Behavioural Questions
While technical skills are key, full-time positions also require cultural fit. Be ready to discuss our previous experiences and how we handle teamwork, conflict, and deadlines. Brush up on the STAR method—Situation, Task, Action, Result—to clearly articulate our past experiences when discussing how we've contributed to a team.