DevOps Engineer AI Agent Platform

DevOps Engineer – AI Agent Platform

Position Overview

We are looking for a DevOps Engineer to design, build, and automate CI/CD and registry workflows for enterprise AI agents. The role will focus on containerized agent delivery, automated version registration, security and evaluation gates, artifact traceability, and reliable promotion of agent versions across environments.

The ideal candidate will have strong experience in DevOps, platform engineering, containerization, CI/CD, AWS, and AI/ML delivery pipelines, with an interest in building modern infrastructure for enterprise AI platforms.

Project Overview

About the Client

Our client is a large global enterprise operating across multiple markets, with a complex technology landscape and a strong focus on digital transformation and innovation. The organization is actively investing in modern cloud, data, and AI capabilities to enable scalable, secure, and highly automated solutions across its business.

About the Project

The project focuses on building an enterprise-grade AI Agent Platform from the ground up. The platform will provide a standardized foundation for developing, deploying, orchestrating, securing, and observing AI agents across multiple teams and use cases.

The initiative covers the full AI agent lifecycle, bringing together:

• Agent orchestration
• CI/CD and platform engineering
• Observability
• Security and governance
• Integrations
• Agent evaluation
• Deployment and environment promotion
• Artifact and version traceability

Engineers joining the project will have the opportunity to influence key architectural and technical decisions and contribute to building a new platform rather than maintaining an existing solution.

Key Responsibilities

• Design and implement CI/CD pipelines for AI agents, including ARM64 container builds, security scanning, AWS ECR publishing, and AgentCore Runtime version creation.
• Build and maintain GitHub Actions workflows supporting matrix builds, parallel execution, and agent-specific validation.
• Integrate CI/CD workflows with the Agent Registry to automatically register agent versions and associated metadata.
• Implement and maintain agent version metadata, including:
• Version ID
• Git SHA
• Container image digest
• Build and registration timestamp
• Evaluation results
• Promotion status
• Tool and policy bindings
• Manage AI agent container images in AWS ECR, including semantic versioning and Git SHA-based tagging strategies.
• Implement automated security scanning within CI/CD pipelines covering vulnerabilities, secrets, compliance requirements, and agent-specific security risks.
• Integrate AI agent evaluation gates into deployment workflows and prevent promotion of versions that fail required quality or security checks.
• Design reliable promotion workflows across development, testing, staging, and production environments.
• Maintain end-to-end traceability between source code, container artifacts, evaluation results, registry records, and deployed agent versions.
• Automate version creation and deployment processes to reduce manual intervention and improve release reliability.
• Collaborate with platform, AI/ML, security, and application engineering teams to establish standardized agent delivery practices.
• Contribute to DevOps standards, automation frameworks, documentation, monitoring, and operational best practices.

Required Skills & Technical Experience

DevOps & CI/CD

• 4+ years of experience in DevOps, Platform Engineering, or a closely related field.
• Strong experience designing and implementing CI/CD pipelines for containerized applications, AI/ML workloads, or similar production systems.
• Hands-on experience with GitHub Actions, including reusable workflows, matrix builds, secrets management, and automated validation.
• Strong understanding of CI/CD automation, artifact management, release strategies, and environment promotion.

Containers & Registries

• Strong experience with Docker/containerized workloads and production container delivery.
• Experience building and publishing ARM64 container images.
• Hands-on experience with AWS ECR or equivalent enterprise container registries.
• Experience implementing container tagging and versioning strategies, including:
• Semantic versioning
• Git SHA-based tags
• Immutable image references
• Container digest traceability

AWS & Cloud

• Strong experience with AWS cloud services and infrastructure.
• Experience with AWS container and deployment services.
• Understanding of IAM, security controls, networking, logging, and cloud-native deployment practices.

Security & Quality Gates

• Experience integrating security scanning into CI/CD pipelines.
• Knowledge of vulnerability scanning, secrets detection, compliance checks, and container security.
• Experience implementing automated quality or evaluation gates that can block artifact promotion when predefined criteria are not met.
• Understanding of secure software supply chain and artifact traceability practices.

AI/ML Platform Engineering

• Experience working with AI/ML pipelines, AI applications, or agent-based systems.
• Understanding of the lifecycle of containerized AI/ML workloads from source code through build, evaluation, registry, deployment, and promotion.
• Familiarity with metadata-driven version management and deployment workflows.

Agent Platform-Specific Requirements

• Experience implementing agent CI/CD pipelines, including container build, security validation, registry publishing, and runtime version creation.
• Experience with Agent Registry integrations and automated agent version registration.
• Understanding of agent-specific security validation, including prompt injection and PII leakage testing.
• Experience designing metadata schemas for agent versions and deployment artifacts.
• Ability to establish traceability between Git commits, container digests, evaluations, registry entries, and deployed versions.

Nice to Have

• Experience working with AWS AgentCore Runtime and its endpoint/version management APIs.
• Experience integrating automated agent evaluation frameworks into CI/CD pipelines.
• Experience implementing GitOps-based promotion patterns for AI agents or ML workloads.
• Experience with LangChain and/or LangGraph agent packaging and deployment.
• Experience with AI agent security and governance frameworks.
• Familiarity with infrastructure-as-code tools such as Terraform or AWS CDK.
• Experience with Kubernetes or other container orchestration platforms.
• Understanding of software supply chain security and artifact provenance.

Education

• Bachelor's degree in Computer Science, Information Technology, Software Engineering, Engineering, or a related field.

Key Competencies

• Strong problem-solving and troubleshooting skills.
• Ability to design scalable and reusable automation.
• Strong understanding of DevOps and platform engineering principles.
• Attention to detail, particularly around security, traceability, and release management.
• Ability to work effectively with AI/ML engineers, software engineers, security teams, and platform teams.
• Strong communication and documentation skills.
• Ability to work in a fast-paced environment and contribute to architectural and technical decisions.

Why This Position

• Opportunity to work on a greenfield enterprise AI Agent Platform.
• Direct involvement in designing and implementing modern AI agent delivery infrastructure.
• Opportunity to influence platform architecture, automation standards, and engineering practices.
• Exposure to AWS, AI agents, CI/CD, security, evaluation, registries, and cloud-native technologies.
• Work alongside multidisciplinary engineering, AI/ML, security, and platform teams.
• Opportunity to build scalable solutions that support AI agent adoption across a large enterprise.