AI Engineer, DevOps Platform & Security
DevOps engineer on Bain's internal Growth AI Performance System team, building and running the cloud infrastructure (Azure/AWS), CI/CD pipelines, and observability that an applied-AI decisioning platform depends on — including monitoring for production LLM and agentic workloads. Based in São Paulo or Warsaw; needs 3+ years in DevOps with Docker, Kubernetes, Python/Bash, and infrastructure-as-code.
- Compensation
- Not disclosed
- Location
- São Paulo, Brazil
- Work setup
- Not specified
- Seniority
- Not specified
- Employment
- Not specified
- Experience
- Not specified
- Category
- Ai engineering
- Posted
Skills
Must have
- Solid foundation in cloud infrastructure on Azure or AWS (compute, networking, storage, managed services)
- Working experience with CI/CD pipelines and deployment automation (testing, artifact management, deployment stages)
- Proficiency with Docker and containerized deployments; working familiarity with Kubernetes in production
- Proficiency in Linux administration and scripting with Python and Bash; disciplined version control for infrastructure code
- Working knowledge of monitoring and alerting tooling: structured logging, metrics collection, alerting rules
- Exposure to or genuine interest in MLOps and AI infrastructure, LLM service deployment/monitoring, and agentic systems in production
- Understanding of cloud-native security fundamentals: IAM, secrets management, network security, DevSecOps
- Active use of AI-assisted development tools
- 3+ years in DevOps, platform engineering, or infrastructure engineering with hands-on CI/CD and cloud infrastructure experience
- Track record contributing to production infrastructure and deployment systems, not just dev/test environments
- Experience in agile, cross-functional product teams; strong troubleshooting across distributed systems
- Based in or able to work from Warsaw or São Paulo near a Bain office
- Associate's/bachelor's degree in computer science, engineering, mathematics, or related field, or equivalent experience
Nice to have
- Experience with LLM service deployment, agentic system infrastructure, or vector database workloads is a strong advantage
Full description
We are proud to be consistently recognized as one of the world's best places to work, a champion of diversity and a model of social responsibility. We are currently ranked the number one consulting firm on Glassdoor's Best Places to Work list and have maintained a spot in the top four since its founding in 2009. Extraordinary teams are at the heart of our business strategy, but these do not happen by chance. They require intentional focus on bringing together a broad set of backgrounds, cultures, experiences, perspectives, and skills in a supportive and inclusive work environment. We hire people with exceptional talent and create an environment in which every individual can thrive professionally and personally.
Who you'll work with
You will be part of a team building Bain's integrated suite of agentic decisioning tools that gives large organizations always-on intelligence across their most important growth decisions. The role sits at an intersection few organizations can offer: the analytical depth and client access of a top-tier consultancy, the technical ambition of a product company, and engineering work at the frontier of applied AI.
You will work inside Bain's standing product team, building software that helps the world's largest companies answer the questions that drive their business: where to invest, where to focus, and how to win. The impact of what you build is direct and immediate, and the platform compounds in value with every release.
The platform has two layers working together: an agentic core and a set of decision modules, each solving a distinct commercial problem. The build lifecycle is connected to the real world: as case teams work alongside clients across industries and geographies, that feedback flows straight back to engineering and into the product. Every client engagement makes the platform smarter, broader, and more resilient.
This is a startup inside an established company. You get genuine early-stage ownership and real influence over architecture and product direction, backed by Bain's global scale, client relationships, and leadership commitment; the pace of a startup with the runway of a global firm.
We are looking for DevOps engineers who see how to make the platform more reliable and resilient and bring that instinct to every sprint without being asked, and who are comfortable with problems that do not have a known answer. The work involves cloud-native infrastructure, CI/CD for a multi-service platform, and deployment problems with no off-the-shelf answer.
Experience supporting agentic systems matters: how AI backend services are deployed and monitored, evaluation pipelines, and the operational demands of production LLM workloads. This is applied AI in production, at scale, with real users depending on what you build. The field is moving quickly and the team is built to move with it, so the willingness to keep learning counts for as much as what you already know.