- Responsibilities:• 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:
o Execution runtimes for autonomous and semi-autonomous agents
o Secure access to data, services, and APIs
o 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.
- Mandatory Skills:
- Amazon Bedrock
- Amazon Elastic Container Service (ECS)
- AWS
- HashiCorp Terraform
- Machine Learning Operations (MLOps)





- Mandatory Skills Description:• 8+ years of experience in DevOps, Platform Engineering, or Site Reliability Engineering roles.
• Deep, hands-on AWS expertise, including services such as:
o EC2, EKS/ECS, VPC, IAM, S3, RDS/DynamoDB, CloudWatch, Lambda
• Solid production experience with Terraform, including:
o Designing modular Terraform architectures
o Managing state, environments, and multi-account setups
• Proven experience rolling out Enterprise-grade Agentic AI infrastructure on top of existing platforms, including:
o Supporting agent execution within established networking, security, and compliance boundaries
o Enabling scalability, observability, and governance for agent behavior
• Hands-on experience supporting agentic SDLC tools and processes, such as:
o AI-assisted coding, testing, and deployment workflows
o 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 Skills Description:• 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.

📌 DevOps + MLOps Engineer (Hyderabad)
🏢 Luxoft
📍 Hyderabad