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 career growth.
- Why this job: Make a tangible 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.
- 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 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 Deployment Engineer - QuantumBlack, AI by McKinsey in London employer: QuantumBlack, AI by McKinsey
At QuantumBlack, AI by McKinsey, we pride ourselves on being an exceptional employer that fosters a high-performance culture where your contributions truly matter. With a strong emphasis on continuous learning and mentorship, you will have unparalleled opportunities for professional growth while collaborating with a diverse global community of experts. Our comprehensive benefits package and commitment to employee well-being ensure that you can thrive both personally and professionally in one of our vibrant European offices.
Contact Detail:
QuantumBlack, AI by McKinsey Recruiting Team
StudySmarter Expert Advice🤫
We think this is how you could land Senior Forward Deployment Engineer - QuantumBlack, AI by McKinsey in London
✨Tip Number 1
Network like a pro! Reach out to people in your field, especially those at QuantumBlack or similar companies. Attend industry events, webinars, or even local meetups to make connections that could lead to job opportunities.
✨Tip Number 2
Prepare for interviews by practising common questions and scenarios related to AI deployment and engineering. Use the STAR method (Situation, Task, Action, Result) to structure your answers and showcase your problem-solving skills.
✨Tip Number 3
Showcase your projects! Whether it's on GitHub or a personal website, having a portfolio of your work can really set you apart. Highlight any experience with cloud systems, Kubernetes, or AI platforms to grab attention.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re genuinely interested in joining our team at QuantumBlack.
We think you need these skills to ace Senior Forward Deployment Engineer - QuantumBlack, AI by McKinsey in London
Some tips for your application 🫡
Show Your Passion:When writing your application, let your enthusiasm for AI and technology shine through. We want to see that you’re not just ticking boxes but genuinely excited about the role and what you can bring to the table.
Tailor Your CV:Make sure your CV is tailored to the job description. Highlight your relevant experience in software engineering, cloud systems, and any hands-on work with Kubernetes or AI platforms. We love seeing how your background aligns with our needs!
Be Clear and Concise:Keep your application clear and to the point. Use straightforward language to describe your skills and experiences. We appreciate a well-structured application that makes it easy for us to see your qualifications at a glance.
Apply Through Our Website:Don’t forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows you’re serious about joining our team!
How to prepare for a job interview at QuantumBlack, AI by McKinsey
✨Know Your Tech Inside Out
Make sure you brush up on your technical skills, especially in Python, cloud systems like AWS or Azure, and Kubernetes. Be ready to discuss your hands-on experience with these technologies and how you've tackled challenges in past deployments.
✨Showcase Your Problem-Solving Skills
Prepare to share specific examples of how you've approached complex issues in non-standard environments. Use the STAR method (Situation, Task, Action, Result) to structure your answers and highlight your structured approach to debugging.
✨Emphasise Continuous Learning
Since the role values a learning culture, be prepared to talk about how you've embraced feedback and adapted your skills over time. Share instances where you've taken the initiative to learn new technologies or methodologies that benefited your team.
✨Communicate Clearly with Stakeholders
Practice explaining complex technical concepts in simple terms, as you'll need to communicate effectively with both technical and non-technical stakeholders. Think of examples where you've successfully delivered training or documentation to help others understand AI-driven applications.
