About the Role

We’re looking for a hands-on Senior AWS DevOps / Platform Engineer to take AI, GenAI and Agentic AI use cases from POC into secure, scalable, observable and production-ready services on AWS. You’ll own the infrastructure, containerisation, CI/CD, security, observability and production operations required to run Agentic AI workloads reliably at scale. This is a hands-on build-and-run engineering role, not an architecture role.

Responsibilities

- Build and operate DEV, TEST and PROD AWS environments for Agentic AI workloads.
- Containerise Agentic AI/Python workloads and deploy using Docker, EKS/ECS and Bedrock AgentCore.
- Build repeatable infrastructure using Terraform/IaC, including networking, IAM/workload identity, KMS, secrets and secure connectivity.
- Build fully automated, secure DevSecOps CI/CD pipelines covering testing, security/container scanning, deployment, promotion and rollback.
- Integrate AI/GenAI evaluation, regression and guardrail gates provided by AI Engineering into CI/CD.
- Configure end-to-end telemetry and observability using OpenTelemetry/ADOT, CloudWatch and AgentCore capabilities.
- Implement SLOs, monitoring, resilience, production readiness and incident/RCA practices.
- Apply FinOps / cloud economics to optimise scalability, utilisation, performance and cost.
- Work in a cooperative, engineering-led environment focused on automation, security-by-design, reliability, experimentation, knowledge sharing and continuous improvement.
- Work closely with AI Engineering, Architecture,



Security and Operations to establish reusable patterns for moving Agentic AI use cases into production quickly and safely.

Required Skills

- Strong hands-on AWS DevOps / Platform Engineering experience.
- Proven experience building AWS environments and taking containerised workloads into live production.
- Strong hands-on Amazon Bedrock and Bedrock AgentCore experience.
- Strong Docker, Kubernetes/EKS and Terraform/IaC expertise.
- Strong CI/CD automation, DevSecOps and AWS security/IAM experience.
- Production experience with OpenTelemetry/ADOT, CloudWatch, monitoring and distributed tracing.
- Strong understanding of SRE practices, including SLOs, resilience, incident management and RCA.
- Bash and/or Python automation skills.
- Practical FinOps / AWS cost optimisation experience.
- Must have personally built, automated, secured, deployed and operated production-grade AWS environments and containerised workloads end-to-end.
- Hands-on Amazon Bedrock and Bedrock AgentCore experience is essential.
- Production AI, GenAI or Agentic AI experience is strongly preferred.
- Infrastructure support, CI/CD-only or non-production experience alone is not sufficient.

Preferred Skills

- AgentOps / production AI operations.
- AWS Control Tower / AWS Organizations / multi-account environments.
- Helm / Argo CD / GitOps.
- Prometheus / Grafana.
- High Availability / Disaster Recovery.
- MCP/tool/API integration exposure.
- Experience working within SAP environments.
- AWS Certified DevOps Engineer – Skilled.
- AWS Certified Solutions Architect – Professional.
- Relevant Kubernetes / Terraform certifications.
- Hands-on production experience takes priority over certifications.

📌 DevOps Engineer (Bengaluru)
🏢 Trigent Software - Professional Services
📍 Bengaluru