Lead Engineer, DevOps Platform & Security (AI)

Location: Based in or able to work from Warsaw, Poland, or São Paulo, Brazil, near a Bain office.

Company

Bain & Company is a global consulting firm building an integrated suite of agentic decisioning tools and a Growth AI Performance System for large organizations.

What you will do

• Design, provision, and operate cloud-based distributed infrastructure across Azure or AWS, including compute, networking, storage, managed databases, container orchestration, and API management.
• Maintain development, staging, and production parity and automate auditable environment promotions using infrastructure as code.
• Build and optimize CI/CD and release engineering for AI backend services, frontend applications, data pipelines, and infrastructure changes, including testing, security scanning, quality gates, rollbacks, and coordinated releases.
• Build observability across platform services and specialized tooling for agentic workloads, including distributed tracing, LLM API latency and cost monitoring, context-passing failure detection, metrics, logging, and alerting.
• Define SLOs, monitor performance, lead incident response, conduct post-incident reviews, and drive reliability improvements.
• Partner with security and AI engineering teams, maintain local development tooling and documentation, mentor a g6 DevOps Engineer, and set platform engineering standards without formal people-management responsibility.

Requirements

• 5 or more years in DevOps, platform engineering, or site reliability engineering with hands-on responsibility for production cloud infrastructure.
• Strong production-scale cloud infrastructure experience across Azure or AWS, including compute, networking, storage, managed databases, container orchestration, and API management.
• Deep proficiency with infrastructure-as-code tooling and experience managing complex, multi-environment infrastructure through code rather than manual configuration.
• Strong CI/CD experience owning deployment pipelines for multi-service platforms, including AI backend services, frontend applications, and data pipelines.
• Practitioner-level Kubernetes experience deploying, operating, and troubleshooting production containerized workloads with latency and reliability requirements.
• Experience building observability for distributed systems using structured logging, metrics, distributed tracing, and alerting; growing expertise in AI and agentic system observability.
• Experience with MLOps and AI infrastructure patterns, including deployment, scaling, and monitoring of LLM API services and infrastructure requirements for vector databases, knowledge graphs, and agentic execution.
• Understanding of IAM, secrets management, network security, compliance, and DevSecOps practices for cloud-native platforms serving enterprise client data.
• Linux administration, infrastructure automation scripting, disciplined version control for infrastructure codebases, active use of AI-assisted tooling, troubleshooting, incident response, agile cross-functional work, and mentoring experience.
• Associate’s or bachelor’s degree in computer science, engineering, mathematics, or a related technical field, or an equivalent combination of education, training, and experience.

Nice to have

• Experience with MLOps or AI platform infrastructure supporting LLM services, agentic systems, or ML pipelines in production.

Culture & Benefits

• Permanent full-time employment within a globally distributed platform team.
• Startup-style ownership and influence over architecture and product direction, backed by Bain’s global scale and client relationships.
• Work on applied AI infrastructure used by large organizations and real client deployments.
• Supportive and inclusive environment focused on diverse backgrounds, cultures, experiences, perspectives, and skills.