{"id":3141391,"url":"https://alion.io/job/kansoft-solutions-pvt-ltd-aws-agentcore-engineer-ai-platform","title":"AWS AgentCore Engineer - AI Platform","company":{"id":3776433,"name":"Kansoft Solutions Pvt Ltd","domain":"kansoftware.com","url":"https://alion.io/company/kansoftware","size_band":"51-200","is_staffing_agency":false,"employer_type":"staffing","is_intermediary":false,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"DevOps","role_family":"DevOps","seniority":"senior","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":17000,"max_usd":40000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":53},"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"AIOps","optional":false},{"name":"Amazon CloudWatch","optional":false},{"name":"AWS","optional":false},{"name":"AWS Bedrock","optional":false},{"name":"AWS Bedrock AgentCore","optional":false},{"name":"AWS CDK","optional":false},{"name":"CI/CD","optional":false},{"name":"CloudFormation","optional":false},{"name":"FinOps","optional":false},{"name":"Function Calling","optional":false},{"name":"Git","optional":false},{"name":"IAM","optional":false},{"name":"Least Privilege","optional":false},{"name":"LLM Guardrails","optional":false},{"name":"Model Context Protocol","optional":false},{"name":"OpenTelemetry","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"Python","optional":false},{"name":"Rest API","optional":false},{"name":"ServiceNow","optional":false},{"name":"Terraform","optional":false}],"status":"live","first_seen_at":"2026-10-23T06:12:50Z","employer_posted_date":null,"last_verified_at":"2026-10-23T06:12:50Z","board_verified":false,"closed_at":null,"days_open":4,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":4},"description":"Job Summary : \n\nKansoft 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.\n\nKey Responsibilities : \n\n- Design, build, and maintain the foundational architecture of an enterprise-grade AI agent platform using AWS AgentCore and Amazon Bedrock.\n\n- Configure and manage agent runtimes, agent registry, deployment workflows, scaling, and lifecycle management.\n\n- Develop and deploy AI agents with secure runtime environments, session management, and appropriate resource isolation.\n\n- Integrate Amazon Bedrock foundation models with AI agents, tools, enterprise data sources, and business applications.\n\n- Implement agent authentication, authorization, identity management, access controls, and secure credential handling.\n\n- Build reusable frameworks and components to support agent registration, versioning, deployment, updates, rollback, and retirement.\n\n- Enable secure agent-to-tool connectivity using Model Context Protocol (MCP) and related integration patterns.\n\n- Integrate AI agents with enterprise platforms such as ServiceNow, Microsoft 365, SAP SuccessFactors, legal repositories, and other business applications.\n\n- Implement guardrails, policy enforcement, human approval workflows, audit trails, and emergency kill-switch mechanisms.\n\n- Collaborate with platform engineering and DevOps teams to implement Infrastructure as Code (IaC), CI/CD pipelines, automated testing, and release management.\n\n- Establish observability using Amazon CloudWatch, OpenTelemetry, CloudTrail, logs, metrics, tracing, and operational dashboards.\n\n- Monitor agent performance, reliability, latency, resource utilization, and operational costs; support FinOps and optimization initiatives.\n\n- Troubleshoot runtime failures, integration issues, access errors, scaling challenges, and production incidents.\n\nRequired Technical Skills : \n\n- Strong hands-on experience with AWS AgentCore and its relevant capabilities, including AgentCore Runtime, Gateway, Identity, Memory, and related services.\n\n- Experience with Amazon Bedrock, foundation models, agent development, tool calling, and agent orchestration.\n\n- Strong AWS cloud fundamentals, including IAM, VPC, networking, security, monitoring, and resource management.\n\n- Experience building and deploying production-grade AI agents and integrating them with enterprise systems.\n\n- Knowledge of MCP architecture, MCP servers, tool integration, and secure connectivity patterns.\n\n- Experience with Python and API development, including REST APIs and service integrations.\n\n- Familiarity with Infrastructure as Code tools such as AWS CDK, CloudFormation, or Terraform.\n\n- Experience with CI/CD pipelines, Git-based version control, automated deployment, and rollback strategies.\n\n- Knowledge of identity management, least-privilege access, secrets management, encryption, and enterprise security controls.\n\n- Experience with observability, distributed tracing, logging, metrics, and production troubleshooting.\n\n- Understanding of AI governance, guardrails, auditability, responsible AI practices, and operational controls.\n\nWhat We Are Looking For : \n\n- A hands-on engineer who can build and operationalize AI agent infrastructure rather than focus solely on AI research or prompt engineering.\n\n- Strong problem-solving and troubleshooting skills.\n\n- Ability to work collaboratively with AI engineering, cloud infrastructure, security, and DevOps teams.\n\n- Good communication skills and the ability to document technical solutions and transfer knowledge.\n\nSkills\nArtificial Intelligence, AWS, Python, Terraform, AIOps, MLOps, Cloud, Cloud Architect - 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