Job Title: Agentic AI Lead
Location: St. Louis or Atlanta
Pay Range: $80/hr - $100/hr
Benefits: Healthcare
About the Job
A large enterprise organization is seeking a Principal Engineer to lead the transformation of its software development lifecycle by building an AI-enabled engineering platform centered on context engineering and advanced code-assist agents. This role is the single-threaded owner responsible for orchestrating, extending, and operationalizing tools like GitHub Copilot, Gemini, Cursor, and similar agentic systems. The goal is to create a highly leveraged engineering environment where AI agents autonomously assist with code generation, testing, incident response, documentation, and workflow execution within a secure, observable, and well-structured operating model. This position requires in-office presence three days per week (Tuesday–Thursday) and does not offer immigration sponsorship.
What You’ll Do
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Define the strategic roadmap for the internal AI engineering platform, treating code-assist agents as first-class products.
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Architect systems for AI agent invocation, context retrieval, and action execution through custom tools and APIs.
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Manage and extend a Model Context Protocol (MCP)-aligned toolset to enable agent interactions with internal and third-party systems.
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Engineer scalable context pipelines that shape agent behavior through centralized, version-controlled custom instructions and connectors.
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Design, test, and optimize prompts, contextual data frameworks, and agent guidance to improve accuracy, efficiency, and reliability.
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Define and monitor KPIs for agentic system performance and implement a comprehensive observability stack.
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Establish platform security, including safeguards for custom tools and APIs, and implement human-in-the-loop guardrails for critical actions.
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Define and enforce code-driven RBAC and least-privilege controls for all agent-invoked actions.
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Demonstrate expertise in cloud-native, distributed microservices architectures.
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Deliver software solutions aligned with standard SDLC practices.
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Build strong relationships with internal stakeholders across product, business, engineering, and operations.
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Communicate complex technical concepts clearly to both technical and non-technical audiences.
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Build and manage high-performing engineering teams that deliver scalable, reliable systems.
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Lead troubleshooting efforts for production and customer issues under pressure.
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Leverage full-stack development skills and extensive experience with public cloud environments.
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Mentor and coach junior engineers and contribute to talent development.
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Drive a data-driven engineering culture with a focus on efficiency and optimization.
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Ensure adherence to secure software development best practices and maintain engineering KPIs across quality, security, and cost.
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Define and report SLAs, SLOs, and SLIs in partnership with product and architecture teams.
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Collaborate with architects, SRE leaders, and other technical stakeholders to shape long-term technical direction.
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Maintain up-to-date technical documentation and runbooks.
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Make architecture decisions related to new features, refactoring, and end-of-life transitions.
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Create and deliver technical presentations to a range of audiences.
Required Skills
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Bachelor’s degree in Computer Science or equivalent experience.
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7+ years of hands-on software engineering experience.
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7+ years of experience with Java, Spring Boot, TypeScript/JavaScript, HTML, and CSS.
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7+ years designing and developing cloud-native solutions.
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7+ years building microservices using Java, Spring Boot, cloud SDKs, and Kubernetes.
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3+ years of experience with advanced code-assist tools, ideally at an expert level.
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3–5+ years building or architecting intelligent agent systems integrated with LLMs.
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Hands-on experience with CI/CD pipelines, GitHub Actions, Jenkins, infrastructure-as-code, Helm, and Terraform.
Preferred Qualifications
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Deep expertise across the GitHub ecosystem, including Actions, Apps, webhooks, and APIs.
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Senior-level proficiency in Python, Go, or Node.js.
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Strong experience designing and consuming RESTful APIs and integrating complex SaaS systems.
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Familiarity with the Model Context Protocol (MCP) and experience creating MCP-aligned services.
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Extensive experience with cloud platforms and Kubernetes.
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Strong systems-thinking ability across the entire SDLC.
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Experience with event-driven architectures, especially those triggered by GitHub events.
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Hands-on experience building LLM-integrated applications.
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Expertise in building tools, APIs, and function-calling interfaces for AI agents.
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Practical experience designing or optimizing RAG systems.
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Ability to orchestrate workflows around existing code-assist agents.
Brilliant Staffing, LLC is an Equal Opportunity Employer and encourages applications from all individuals regardless of race, color, religion, gender, gender identity, sexual orientation, national origin, disability, or veteran status.