What are the responsibilities and job description for the Principal Agentic AI Engineer position at Brilliant®?
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
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
- Define the strategic roadmap for the internal AI engineering platform, treating code-assist agents as first-class products.
- Architect systems for AI agent invocation, context retrieval, and action execution through custom tools and APIs.
- Manage and extend a Model Context Protocol (MCP)-aligned toolset to enable agent interactions with internal and third-party systems.
- Engineer scalable context pipelines that shape agent behavior through centralized, version-controlled custom instructions and connectors.
- Design, test, and optimize prompts, contextual data frameworks, and agent guidance to improve accuracy, efficiency, and reliability.
- Define and monitor KPIs for agentic system performance and implement a comprehensive observability stack.
- Establish platform security, including safeguards for custom tools and APIs, and implement human-in-the-loop guardrails for critical actions.
- Define and enforce code-driven RBAC and least-privilege controls for all agent-invoked actions.
- Demonstrate expertise in cloud-native, distributed microservices architectures.
- Deliver software solutions aligned with standard SDLC practices.
- Build strong relationships with internal stakeholders across product, business, engineering, and operations.
- Communicate complex technical concepts clearly to both technical and non-technical audiences.
- Build and manage high-performing engineering teams that deliver scalable, reliable systems.
- Lead troubleshooting efforts for production and customer issues under pressure.
- Leverage full-stack development skills and extensive experience with public cloud environments.
- Mentor and coach junior engineers and contribute to talent development.
- Drive a data-driven engineering culture with a focus on efficiency and optimization.
- Ensure adherence to secure software development best practices and maintain engineering KPIs across quality, security, and cost.
- Define and report SLAs, SLOs, and SLIs in partnership with product and architecture teams.
- Collaborate with architects, SRE leaders, and other technical stakeholders to shape long-term technical direction.
- Maintain up-to-date technical documentation and runbooks.
- Make architecture decisions related to new features, refactoring, and end-of-life transitions.
- Create and deliver technical presentations to a range of audiences.
- Bachelor’s degree in Computer Science or equivalent experience.
- 7 years of hands-on software engineering experience.
- 7 years of experience with Java, Spring Boot, TypeScript/JavaScript, HTML, and CSS.
- 7 years designing and developing cloud-native solutions.
- 7 years building microservices using Java, Spring Boot, cloud SDKs, and Kubernetes.
- 3 years of experience with advanced code-assist tools, ideally at an expert level.
- 3–5 years building or architecting intelligent agent systems integrated with LLMs.
- Hands-on experience with CI/CD pipelines, GitHub Actions, Jenkins, infrastructure-as-code, Helm, and Terraform.
- Deep expertise across the GitHub ecosystem, including Actions, Apps, webhooks, and APIs.
- Senior-level proficiency in Python, Go, or Node.js.
- Strong experience designing and consuming RESTful APIs and integrating complex SaaS systems.
- Familiarity with the Model Context Protocol (MCP) and experience creating MCP-aligned services.
- Extensive experience with cloud platforms and Kubernetes.
- Strong systems-thinking ability across the entire SDLC.
- Experience with event-driven architectures, especially those triggered by GitHub events.
- Hands-on experience building LLM-integrated applications.
- Expertise in building tools, APIs, and function-calling interfaces for AI agents.
- Practical experience designing or optimizing RAG systems.
- Ability to orchestrate workflows around existing code-assist agents.
Salary : $80 - $100
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