AWS AgentCore Engineer - AI Platform
First seen by Alion on Oct 23, 2026.
Job Summary :
Kansoft is looking for an experienced AWS AgentCore Engineer to build and operationalize the foundation of a governed Enterprise AI Platform on AWS. The role focuses on developing scalable, secure, and production-ready AI agent infrastructure using AWS AgentCore and Amazon Bedrock, enabling enterprises to build, deploy, manage, and monitor AI agents at scale.
Key Responsibilities :
- Design, build, and maintain the foundational architecture of an enterprise-grade AI agent platform using AWS AgentCore and Amazon Bedrock.
- Configure and manage agent runtimes, agent registry, deployment workflows, scaling, and lifecycle management.
- Develop and deploy AI agents with secure runtime environments, session management, and appropriate resource isolation.
- Integrate Amazon Bedrock foundation models with AI agents, tools, enterprise data sources, and business applications.
- Implement agent authentication, authorization, identity management, access controls, and secure credential handling.
- Build reusable frameworks and components to support agent registration, versioning, deployment, updates, rollback, and retirement.
- Enable secure agent-to-tool connectivity using Model Context Protocol (MCP) and related integration patterns.
- Integrate AI agents with enterprise platforms such as ServiceNow, Microsoft 365, SAP SuccessFactors, legal repositories, and other business applications.
- Implement guardrails, policy enforcement, human approval workflows, audit trails, and emergency kill-switch mechanisms.
- Collaborate with platform engineering and DevOps teams to implement Infrastructure as Code (IaC), CI/CD pipelines, automated testing, and release management.
- Establish observability using Amazon CloudWatch, OpenTelemetry, CloudTrail, logs, metrics, tracing, and operational dashboards.
- Monitor agent performance, reliability, latency, resource utilization, and operational costs; support FinOps and optimization initiatives.
- Troubleshoot runtime failures, integration issues, access errors, scaling challenges, and production incidents.
Required Technical Skills :
- Strong hands-on experience with AWS AgentCore and its relevant capabilities, including AgentCore Runtime, Gateway, Identity, Memory, and related services.
- Experience with Amazon Bedrock, foundation models, agent development, tool calling, and agent orchestration.
- Strong AWS cloud fundamentals, including IAM, VPC, networking, security, monitoring, and resource management.
- Experience building and deploying production-grade AI agents and integrating them with enterprise systems.
- Knowledge of MCP architecture, MCP servers, tool integration, and secure connectivity patterns.
- Experience with Python and API development, including REST APIs and service integrations.
- Familiarity with Infrastructure as Code tools such as AWS CDK, CloudFormation, or Terraform.
- Experience with CI/CD pipelines, Git-based version control, automated deployment, and rollback strategies.
- Knowledge of identity management, least-privilege access, secrets management, encryption, and enterprise security controls.
- Experience with observability, distributed tracing, logging, metrics, and production troubleshooting.
- Understanding of AI governance, guardrails, auditability, responsible AI practices, and operational controls.
What We Are Looking For :
- A hands-on engineer who can build and operationalize AI agent infrastructure rather than focus solely on AI research or prompt engineering.
- Strong problem-solving and troubleshooting skills.
- Ability to work collaboratively with AI engineering, cloud infrastructure, security, and DevOps teams.
- Good communication skills and the ability to document technical solutions and transfer knowledge.
Skills
Artificial Intelligence, AWS, Python, Terraform, AIOps, MLOps, Cloud, Cloud Architect - AI/ML