Lead AI Agent Engineer

CGI•Lafayette, LA

3d•Onsite

About The Position

CGI is seeking a Lead AI Agent Engineer to implement, administer, secure, and support enterprise AI coding agent and developer productivity platforms within a large scale financial services environment. The ideal candidate has experience taking AI coding agent capabilities beyond proofs of concept into secure, production enterprise environments. This individual will work independently on complex integrations, establish technical standards and controls, develop validation and automation frameworks, and provide technical leadership to engineering teams adopting AI assisted development technologies. This position is required in one of the following locations: Birmingham, AL, Knoxville, TN or Lafayette, LA

Requirements

5+ years hands on experience implementing and administering enterprise AI coding platforms, including GitHub Copilot, OpenAI Codex/coding agents, or comparable technologies.
Strong experience building and configuring AI agents, custom assistants, agent tools, integrations, context management, orchestration, and multi agent workflows.
Hands on knowledge of Model Context Protocol (MCP), including MCP server implementation, authentication, authorization, permissions, identity propagation, credential management, and secure tool access.
Strong Python development skills, including REST APIs, automation utilities, integration services, agent services, test harnesses, and validation frameworks.
Strong AWS experience, particularly Amazon Bedrock, Bedrock Agents, Bedrock AgentCore, IAM, Lambda, API Gateway, ECS, CloudWatch, Secrets Manager/Parameter Store, ALB, and VPC/networking.
Strong understanding of enterprise identity and access management (IAM), including OAuth 2.0, OIDC, SAML, SSO, SCIM, RBAC, JWT, service identities, AWS IAM/Identity Center, and Active Directory/Entra ID.
Experience implementing least privilege security controls for autonomous agents, users, repositories, APIs, and tools.
Experience validating AI agent security, including authorization boundaries, token handling, secrets exposure, privilege escalation, cross user/project access, and prompt injection/tool abuse scenarios.
Experience developing automated agent evaluation, regression testing, security validation, or test frameworks.
Experience configuring enterprise policies, repository access, model settings, agent permissions, usage controls, and security controls for developer AI platforms.
Demonstrated experience supporting production developer platforms or AI/ML platforms used across multiple engineering teams.
Ability to troubleshoot complex cloud, AI agent, identity, API, and platform integrations.
Technical leadership experience supporting complex enterprise implementations and establishing engineering standards.

Nice To Haves

Experience with Bash/Shell scripting or PowerShell.
Experience with asynchronous Python, structured logging, and Python API frameworks.

Responsibilities

Implement, administer, secure, and support enterprise AI coding agent and developer productivity platforms.
Take AI coding agent capabilities beyond proofs of concept into secure, production enterprise environments.
Work independently on complex integrations.
Establish technical standards and controls.
Develop validation and automation frameworks.
Provide technical leadership to engineering teams adopting AI assisted development technologies.
Support production AI agent capabilities across the software development lifecycle, including platform configuration, agent integrations, access controls, functional and security validation, troubleshooting, and ongoing operational management.
Implement least privilege security controls for autonomous agents, users, repositories, APIs, and tools.
Validate AI agent security, including authorization boundaries, token handling, secrets exposure, privilege escalation, cross user/project access, and prompt injection/tool abuse scenarios.
Develop automated agent evaluation, regression testing, security validation, or test frameworks.
Configure enterprise policies, repository access, model settings, agent permissions, usage controls, and security controls for developer AI platforms.
Support production developer platforms or AI/ML platforms used across multiple engineering teams.
Troubleshoot complex cloud, AI agent, identity, API, and platform integrations.
Establish engineering standards.