Senior DevOps / Platform Engineer

About the Role Senior DevOps / Platform Engineer with deep AWS expertise to evolve and operate Luxoft's core cloud platform, enabling Enterprise-grade Agentic AI capabilities while ensuring stability, scalability, and developer enablement. This role focuses on platform reliability and building a foundation for AI-augmented SDLC workflows, without compromising operational excellence.

What You'll Do

• Design, build, and operate a shared AWS cloud platform that supports both traditional services and agentic AI workloads.
• Own and evolve Infrastructure as Code (IaC) using Terraform, ensuring consistency, security, and repeatability across environments.
• Extend existing infrastructure to support Enterprise-grade Agentic AI systems, including: Execution runtimes for autonomous and semi-autonomous agents; Secure access to data, services, and APIs; Platform-level guardrails for safety, governance, and cost control.
• Build platform abstractions, templates, and tooling that enable teams to safely consume agentic capabilities.
• Support and integrate agentic SDLC tools and processes, including AI-assisted development, testing, and release automation.
• Develop and maintain CI/CD pipelines for both traditional applications and AI-driven components.
• Implement platform-level observability (metrics, logs, traces) across services and agent workloads.
• Enforce security and compliance best practices (IAM, secrets management, encryption, least privilege).
• Collaborate closely with application, AI/ML, and security teams to improve developer experience and platform reliability.
• Act as a technical leader in architecture discussions, platform standards, and operational readiness.

What We're Looking For

• 8+ years of experience in DevOps, Platform Engineering, or Site Reliability Engineering roles.
• Deep, hands-on AWS expertise, including EC2, EKS/ECS, VPC, IAM, S3, RDS/DynamoDB, CloudWatch, Lambda.
• Strong production experience with Terraform, including: Designing modular Terraform architectures; Managing state, environments, and multi-account setups.
• Proven experience rolling out Enterprise-grade Agentic AI infrastructure on top of existing platforms, including: Supporting agent execution within established networking, security, and compliance boundaries; Enabling scalability, observability, and governance for agent behavior.
• Hands-on experience supporting agentic SDLC tools and processes, such as AI-assisted coding, testing, and deployment workflows.
• Agent-based automation within CI/CD and operational processes.
• Solid understanding of Linux, networking, and cloud security fundamentals.
• Experience with containerized and Kubernetes-based platforms (Docker, EKS).
• Familiarity with MLOps or AI platform components (model serving, vector databases, feature stores).

Nice to Have

• Experience designing internal developer platforms (IDPs).
• Knowledge of policy-as-code and governance frameworks (OPA, SCPs, tagging strategies).
• AWS certifications (Solutions Architect, DevOps Engineer).
• Experience operating platforms at enterprise scale or in regulated environments.