AI Agent Engineer - Full Time

Crowdplum Global Services LLC
Virginia Beach, VA, United States
5 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Working hours
Regular working hours
Job source

Tech stack

Active Directory Application Programming Interfaces (APIs) Artificial Intelligence Amazon Web Services User Authentication Bash Shell Cloud Computing Computer Programming System Configuration Identity and Access Management Python (Programming Language) Networking Basics
+28 more
OAuth OpenID Windows PowerShell Systems Development Life Cycle Role-Based Access Control Openid Connect Azure Machine Learning Security Assertion Markup Language (SAML) Shell Script Single Sign-On Software Engineering Systems Integration Data Logging Load Balancing GitHub Copilot Multi-Agent Systems AI Coding Agents Amazon Virtual Private Cloud (VPC) Agentic-AI AI Platforms Amazon Bedrock Virtual Agents Functional Programming Cloudwatch Api Gateway Restful APIs Model Context Protocol OpenAI Codex

Requirements

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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