AWS Agent Core with AI Experience

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.

The ideal candidate will have hands-on experience in AWS cloud engineering, AI agent runtime environments, lifecycle management, enterprise integrations, security, and platform automation.

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.
• Support proof of concepts, production deployments, technical documentation, knowledge transfer, and operational readiness.

Required Technical Skills

• Strong hands-on experience with AWS AgentCore and its relevant capabilities, including AgentCore Runtime, Gateway, Identity, Memory, and related services as applicable.
• 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.

Good to Have

• Experience implementing enterprise AI platforms in regulated or large-scale environments.
• Familiarity with ServiceNow, Microsoft 365, SAP SuccessFactors, and legal or document management systems.
• Experience with Amazon CloudWatch, AWS CloudTrail, OpenTelemetry, and cost monitoring.
• Exposure to Amazon Bedrock Guardrails, agent evaluation, prompt/version management, and AI security testing.
• Familiarity with Kiro, Amazon Quick Suite, or citizen-developer enablement platforms.
• Experience with multi-agent architectures, asynchronous workflows, and event-driven integrations.
• Knowledge of production support, disaster recovery, high availability, and platform reliability engineering.

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

Application Question(s):

• What is your Current CTC?
• What is your Expected CTC?
• What is your Current Notice period?

Work Location: Remote