Senior Forward Deployed Engineer

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. Your 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.

Within our São Paulo office, you’ll collaborate with engineers, product teams, and technical experts across our global community. Beyond platform deployments, you’ll work with data scientists, machine learning engineers, designers, and technologists on interdisciplinary initiatives, contributing to a broader ecosystem of AI innovation. You’ll help operationalize advanced AI systems across industries, driving successful delivery, validation, and adoption in client environments. You’ll also support team knowledge‑sharing—documenting patterns, refining delivery practices, and supporting colleagues across engagements.

Your Qualifications and Skills

• Bachelor’s or Master’s degree 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, Infrastructure as Code (e.g., GitHub Actions, GitLab CI, Terraform, Ansible, Helm), deployment standards, runbook development, and automation frameworks
• 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, in