Vertical Relevance is seeking an experienced Sr. AI/ML Amazon Agentcore to join our team as a full-time, remote employee. In this role, you will design, build, and deploy scalable data solutions on AWS while collaborating directly with customers to modernize their data platforms and cloud capabilities.
We are seeking an experienced Senior, AgentCore AI/ML Lead to serve as the technical leader for a high-profile GenAI platform initiative. This role will drive the architecture, implementation, governance, and operationalization of AI agents within an enterprise-scale AWS environment.
This is not a traditional infrastructure or DevOps position. The ideal candidate must have firsthand Amazon Bedrock AgentCore implementation experience and a proven track record building, deploying, and governing AI agents in production environments.
Role Overview
As the AgentCore AI/ML Lead, you will own the AgentCore platform workstream, defining and implementing the architecture that underpins the organization's GenAI LaunchPad ecosystem. You will work closely with AWS specialists, business stakeholders, and engineering teams to deliver scalable, secure, and governed AI agent solutions.
You will provide technical leadership while remaining firsthand in the design, configuration, and deployment of AI agents, knowledge bases, action groups, and supporting platform services.
Firsthand experience implementing Amazon Bedrock AgentCore in enterprise environments.
Experience building and configuring:
- AI Agents
- Knowledge Bases
- Action Groups
- Agent Orchestration Workflows
- Experience deploying and managing containerized workloads on Amazon ECS
- API Gateway design and implementation
- Authentication and authorization mechanisms
- Runtime configuration management
- IAM policies and controls
- Agent guardrails
- Cross-service and cross-agent invocation governance
- Platform security best practices.
Ability to operate in evolving environments with limited upfront requirements and collaborate effectively with AWS teams and customer stakeholders
Preferred Qualifications
- Terraform (Infrastructure as Code)
- MCP (Model Context Protocol) server implementation experience
- Enterprise AI platform architecture experience
- GenAI governance and responsible AI controls
AI Agent Development
- Design, build, and configure AI agents using Amazon Bedrock AgentCore
- Develop and manage knowledge bases and action groups
- Implement scalable agent architectures and best practices
- Lead strategic architecture initiatives, including:
- HTTP API migration
- MCP server deployment and integration
- Agent platform standardization
- Guide ECS-based deployment strategies and operational models
- Design and implement enterprise AgentCore guardrails
- Define IAM governance and agent interaction controls
- Build an enterprise-grade "Agent Kill Switch" capability for emergency shutdown and immediate runtime access revocation
- Establish a centralized registry for:
- AI agents
- Foundation models
- Reusable blueprints
- Platform standards and governance artifacts
- Provide technical direction to DevOps and implementation resources
- Collaborate with AWS account teams during technical deep-dive sessions
- Support program governance, prioritization, and delivery planning
- Amazon Bedrock AgentCore
- Amazon ECS
- API Gateway
- IAM
- Terraform
- MCP (Model Context Protocol)
- AWS Secrets Manager
Ideal Candidate
You are a technical leader who combines deep AWS AI expertise with hands-on delivery experience. You have successfully implemented AgentCore-based solutions, understand enterprise governance requirements, and can guide teams through complex AI platform initiatives while remaining actively involved in the technical implementation.
If you have real-world Amazon Bedrock AgentCore implementation experience and are passionate about shaping the future of enterprise AI, we'd love to hear from you.
- At Vertical Relevance, we believe in delivering with excellence through teamwork, automating everything, constantly learning, and taking ownership of customer outcomes.
- We help organizations navigate complex transformation initiatives across people, processes, technology, and data. Our team brings deep industry expertise and a practical, results-oriented approach to every engagement.
- If you are an AWS data engineer who enjoys solving challenging problems, collaborating directly with customers, and building modern cloud data solutions, we’d love to hear from you.
- Vertical Relevance is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected veteran status, age, or any other characteristic protected by applicable law.
Skills Required
- Firsthand experience implementing Amazon Bedrock AgentCore in enterprise environments
- Experience building and configuring AI agents, knowledge bases, action groups, and agent orchestration workflows
- Experience deploying and managing containerized workloads on Amazon ECS
- Strong background in API Gateway design and implementation
- Experience with authentication and authorization mechanisms
- Experience with runtime configuration management
- Security and governance expertise, including IAM policies, agent guardrails, and cross-service or cross-agent invocation controls
- Technical leadership experience directing engineering and DevOps resources
- Ability to work with evolving requirements and collaborate with AWS teams and customer stakeholders
- Terraform infrastructure-as-code experience
- MCP server implementation experience
- Enterprise AI platform architecture experience
- GenAI governance and responsible AI controls experience
What We Do
Vertical Relevance was founded to help business leaders drive value through the design and delivery of effective transformation programs across people, processes, and systems. We focus on new generation processes and technologies and combine with a superior level of industry experience to bring firms gains in productivity, visibility and effectiveness.
