Senior Engineer, Agentic Engineering Governance, Open Source

College Board•Remote - Virginia, VA

2d•$153,000 - $166,000•Remote

About The Position

The Platform Operations team builds solutions that elevate engineering practices across cloud infrastructure, architecture, networking, CI/CD, infrastructure as code, and developer experience. The team operationalizes platforms within College Board’s AWS ecosystem and leads the organization’s approach to agentic and AI-assisted software development. The Senior Engineer, Agentic Engineering Governance, Open Source sets standards for how College Board engineers use AI coding agents and agentic development tools safely, responsibly, and effectively. The role combines hands-on engineering with governance for open-source software, including license compliance, dependency risk, and review of externally published code. The engineer works closely with Security, Legal, Architecture, and developers to establish guardrails, policies, tools, and processes that support responsible adoption of AI coding assistants. The position designs and implements controls for AI agents’ interactions with source code, infrastructure, and production systems; builds tooling for sandboxing, audit logging, and rollback; evaluates emerging tools and frameworks; and contributes to cloud engineering strategy and operations. It also establishes organization-wide standards and acceptable-use policies, authors documentation and training, mentors team members, and serves as an escalation point for governance questions. The role participates in agile ceremonies, peer reviews, production issue resolution, and the team’s daytime on-call rotation. This is a full-time remote role. Candidates who live near College Board offices may choose a hybrid schedule with in-office work on Tuesdays and Wednesdays. Employees are occasionally required to travel for business purposes.

Requirements

At least 5 years of experience with Infrastructure as Code, CI/CD frameworks, immutable infrastructure, automation, orchestration, and modern DevOps patterns.
Significant hands-on experience with AI coding agents or assistants, such as Claude Code, GitHub Copilot, Cursor, or Windsurf, or other LLM-based developer tooling.
Experience with LLM platforms and APIs such as Anthropic Claude or OpenAI, including agent orchestration and tool-use concepts such as function calling and MCP.
Understanding of AI/LLM security considerations, including prompt injection, data exfiltration, permission scoping, and sandboxing.
Experience establishing technical standards, guardrails, or review processes across an engineering organization, in responsible AI governance or an adjacent discipline such as security.
Technical knowledge of cloud computing, DevOps, and microservices, with strong experience in distributed cloud infrastructure.
A strong background in a programming language such as Python, JavaScript, React.js/Node.js, or Java, and the ability to learn new languages quickly.
Excellent communication, collaboration, and documentation skills, including the ability to present AI governance topics in business-friendly and user-friendly language to non-technical stakeholders.
Experience supporting developers as internal customers, gathering their requirements and feedback, and earning adoption of standards.
Curiosity and discipline to research emerging technologies, standards, and products, and the ability to prioritize and execute in a high-pressure environment.
Passion for expanding educational and career opportunities and mission-driven work.
Authorization to work in the United States for any employer.
Curiosity and enthusiasm for emerging technologies, willingness to experiment with and adopt new AI-driven solutions, and comfort learning and applying digital tools independently and proactively.
Clear and concise written and verbal communication skills.
A learner’s mindset and commitment to growth, including welcoming diverse perspectives, giving and receiving respectful feedback, and continuously improving through iterative learning and user input.
Drive for impact and excellence, including solving complex problems, making data-informed decisions, prioritizing effectively, and improving through learning, user input, and external benchmarking.
A collaborative and empathetic approach, including working across differences, fostering trust, and contributing to shared success.

Nice To Haves

Experience with AWS services such as Lambda, SNS, SQS, S3, Step Functions, EC2, ECS, VPC, IAM, CloudWatch, and DynamoDB.
Experience building event-driven cloud-based serverless applications.

Responsibilities

Design and implement guardrails, permission models, and policy-as-code controls governing how AI coding agents interact with source code, infrastructure, and production systems.
Build solutions using Agile, CI/CD, and DevOps best practices.
Build and maintain tooling for sandboxing, audit logging, and rollback of agent-driven code and infrastructure changes.
Develop the skills needed to work in an agile, poly-skilled development environment, including hands-on use of agentic coding tools.
Serve as a subject matter expert in cloud networking, API integrations, infrastructure resiliency, cloud design, and agentic and AI-assisted development patterns.
Write code to automate the infrastructure lifecycle and create and support internal tools using IaC and CLIs.
Evaluate and pilot agentic programming tools, frameworks, and protocols, and make adoption recommendations.
Partner with domain subject matter experts in delivery engineering, security, infrastructure, network, observability, and operations to analyze agentic tooling capabilities and risks.
Contribute thought leadership and design and implementation of tools and processes for the Cloud Engineering Program.
Participate in Enterprise Architecture Review, focusing on proposals involving AI coding agents and agentic tooling.
Establish and maintain organization-wide standards, guardrails, and acceptable-use policies for agentic and AI-assisted software development.
Partner with Security, Legal/Compliance, and Architecture Review stakeholders to assess risk and approve new AI coding agent use cases.
Research emerging agentic and AI development technologies and recommend approaches that improve safety, cost effectiveness, and systems flexibility.
Author documentation, playbooks, and governance frameworks for developers using AI coding assistants.
Participate in agile scrum ceremonies and contribute to team deliverables.
Participate in peer reviews of software engineering artifacts, including code produced or assisted by AI agents.
Help identify and resolve production and production-like issues, including issues arising from agentic tooling, as part of the daytime on-call rotation.
Mentor team members in safe, effective, and compliant use of agentic coding tools.
Design and deliver training materials and office hours to help developers adopt agentic engineering practices.
Lead technical efforts and mentor technical staff in developing and using technology architectures and solutions, primarily for agentic engineering governance for open-source software.
Serve as an escalation point for questions about AI coding tool policy and governance.