Principal Forward Deployed Engineer - QuantumBlack Studio

• 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.

As a Principal Forward Deployed Engineer, you'll lead the deployment and scaling of EcliptOS— QuantumBlack's AI Operating System — a next-generation platform designed to connect strategy to execution through agentic systems. This role is uniquely field-facing. 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 the role. 

This role sits at the intersection of software engineering and infrastructure, bringing EcliptOS into real-world environments and ensuring it works at scale. You'll be at the center of how the platform is deployed, adopted, and operated, helping organizations translate complex AI strategies into practical, high-impact solutions. 

You'll take ownership of the EcliptOS 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. 

The 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 EcliptOS is 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 this 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 EcliptOS 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 EcliptOS 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 São Paulo, you'll work closely with engineers, product teams, and technical experts across QuantumBlack's global community. Beyond leading EcliptOS 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.

• Bachelor's or Master's degree 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 skills, including 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
• Strong verbal and written communication skills in English and Portuguese