Why This Role Stands Out
This hybrid AI Agent Engineer role offers exciting opportunities to lead the implementation and administration of cutting-edge AI coding agents within an enterprise environment, fostering significant technical leadership and impact. If you have deep hands-on experience with AI coding technologies and a passion for driving innovation in developer productivity, you'll thrive in this position. Apply now to contribute to a forward-thinking team and shape the future of AI-assisted development.
Quick Overview
Job Description
Role: AI Agent Engineer.
Location : VA
Job Description:
We are seeking a senior/lead-level engineer with deep hands-on experience in AI coding agents, developer productivity platforms, agent administration, security, and cloud infrastructure.
This resource will help lead the implementation, administration, functional validation, security validation, and operational management of enterprise coding-agent capabilities. The individual should be capable of working independently, troubleshooting complex integrations, establishing technical standards, and providing technical leadership to engineering teams adopting coding agents.
The ideal candidate should have experience operating AI coding technologies in enterprise production environments, rather than solely developing proofs of concept.
Core Qualifications
- AI Coding Agents and Developer AI Platforms
- Deep hands-on experience with OpenAI Codex / coding agents and GitHub Copilot, including implementation, configuration, administration, troubleshooting, and enterprise deployment. Experience configuring and administering capabilities such as: Organization and enterprise-level policies User and group access Repository access Agent permissions Model configuration Tool access
- Policy enforcement Usage controls Enterprise security controls Experience implementing and supporting coding-agent workflows across the software development lifecycle (SDLC). Ability to assess coding-agent behavior from both a functional and administrative/platform perspective. Agent Engineering
- Strong hands-on experience designing, configuring, and building AI agents, including:
- Agent configuration and orchestration Custom coding agents GPTs / custom assistants Agent tools and tool integrations Plugins, Skills, or equivalent extensibility mechanisms Prompt and instruction architecture Agent context management Tool selection and tool execution Multi-agent or orchestrated agent workflows MCP Model Context Protocol
- Strong working knowledge of Model Context Protocol (MCP), including experience building and securing MCP servers.
Experience should include:
MCP scopes and permissions Authentication and authorization Fine-grained authorization Identity propagation Credential handling Secure access to enterprise APIs and systems Restricting agent access using least-privilege principles
Experience designing security boundaries around MCP tools is highly desirable.
Identity, Authentication, and Authorization
Deep understanding of enterprise identity and access management, with hands-on experience implementing several of the following:
SSO, SAML, OAuth 2.0, OpenID Connect (OIDC), Identity Providers (IdP), SCIM provisioning, AWS IAM, AWS IAM Identity Center, Microsoft Active Directory / Entra ID, Bearer tokens, JWT tokens, Service identities, Role-based access control (RBAC), Fine-grained authorization Candidates should understand authentication versus authorization and be capable of designing identity flows for both human users and autonomous agents.
Experience implementing least-privilege access for AI agents is strongly preferred.
AWS and AI Platform Experience
Strong working knowledge of AWS, including hands-on experience with: Amazon Bedrock, Amazon Bedrock Agents, Amazon Bedrock Agent Core, IAM roles and policies, ECS, Application Load Balancer (ALB) Lambda, API Gateway, CloudWatch, Secrets Manager and/or Parameter Store, VPC/networking fundamentals, Programming
Strong proficiency in Python is required.
Candidates should be comfortable developing: REST APIs, Agent services, Automation utilities, Integration services, Test harnesses, Validation frameworks Experience with asynchronous Python, API development frameworks, and structured logging is preferred.
Security and Authorization Validation
Unauthorized repository access
Tool authorization MCP permission boundaries Identity propagation Token handling Privilege escalation Least-privilege enforcement Secrets exposure Cross-user or cross-project access Prompt-injection/tool-abuse scenario Experience developing automated agent evaluation frameworks, test harnesses, or regression suites is strongly preferred.
Preferred / Nice-to-Have Qualifications
Shell scripting / Bash PowerShell Prompt-injection and AI security testing Experience Profile
- Preference should be given to candidates who can demonstrate:
- Significant recent hands-on experience with GitHub Copilot or comparable enterprise AI coding platforms.
- Hands-on experience with OpenAI Codex or production coding-agent technologies.
- Multiple years of experience engineering and operating enterprise developer platforms, cloud platforms, or AI/ML platforms.
- Production experience administering developer-facing technology used by multiple engineering teams.
- Evidence of leading technically complex implementations rather than participating solely as an individual application developer.
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