Senior AWS DevOps / Platform Engineer - Agentic AI Production (26-02956) -

JOB DESCRIPTION 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.

AWS | Bedrock | AgentCore | Terraform | EKS | CI/CD | DevSecOps

What You'll Do

• 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.

What You'll Bring

• 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.

Production Experience – Essential

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.

Team & Culture

Work in a collaborative, engineering-led environment focused on automation, security-by-design, reliability, experimentation, knowledge sharing and continuous improvement.

You'll work closely with AI Engineering, Architecture, Security and Operations to establish reusable patterns for moving Agentic AI use cases into production quickly and safely.

Good to Have

• 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

Preferred Certifications

• AWS Certified DevOps Engineer – Professional
• AWS Certified Solutions Architect – Professional
• Relevant Kubernetes / Terraform certifications

Hands-on production experience takes priority over certifications.