Position : Senior AWS DevOps / Platform Engineer (Agentic AI Infrastructure).

Location : Hybrid (Pan-India).

About the Client & Role Context :

Our client is advancing its digital transformation by operationalizing next-generation Agentic AI and Autonomous Workflows. Moving beyond basic LLM wrappers, they are deploying production-ready AI agents integrated deep within enterprise cloud backends. We are seeking a hands-on Senior AWS DevOps / Platform Engineer who will own the execution pipeline to transition Agentic AI workloads from Proof-of-Concept (POC) into secure, scalable, and observable AWS production environments. This is a pure build-and-run engineering role focused on high reliability and cloud economics.

Core Responsibilities :

- Build, secure, and operate DEV, TEST, and PROD AWS cloud environments dedicated to Agentic AI and Python microservices.

- Containerize agentic AI systems using Docker, Amazon EKS/ECS, and Amazon Bedrock AgentCore.

- Define and maintain infrastructure-as-code using Terraform, enforcing zero-trust networking, IAM workload identities, and KMS key management.

- Design DevSecOps CI/CD pipelines incorporating static code analysis, vulnerability scanning, continuous integration, and dynamic AI evaluation/guardrail gates.

- Implement end-to-end telemetry utilizing OpenTelemetry (ADOT), Amazon CloudWatch, and distributed tracing across agent sessions.

- Establish SRE practices including Service Level Objectives (SLOs), automated failure domain isolations, and root-cause analysis (RCA) frameworks.

- Apply FinOps practices to optimize AWS resource utilization, token consumption costs, and container execution performance.

Required Qualifications & Experience :

- 6+ years of hands-on experience in AWS Platform Engineering, DevOps, or Site Reliability Engineering.

- Demonstrated experience delivering containerized Python/Node applications into live AWS production.

- Direct production exposure to Amazon Bedrock and/or Bedrock AgentCore frameworks.

- Deep technical expertise in Kubernetes (EKS), Docker, and Terraform IaC.

- Advanced pipeline automation skills using GitHub Actions, GitLab CI, or Jenkins with integrated DevSecOps scanning.

- Strong proficiency in OpenTelemetry (ADOT) or enterprise APM tools for distributed tracing.

- Practical automation skills using Python and Bash scripting.

- Strong grasp of FinOps principles within AWS cloud ecosystems.

Preferred Qualifications :

- Experience with GitOps (ArgoCD / Helm), AgentOps, or MCP tool integrations.

- Working knowledge of multi-account AWS architectures (Control Tower, AWS Organizations).

- Certifications : AWS Certified DevOps Engineer Professional or AWS Certified Solutions Architect Professional.