AI Governance Engineer

As MISO's AI Governance Engineer
, you will help build and evolve the enterprise AI governance framework as the organization expands its use of generative and agentic AI. In this role, you will develop practical guardrails, controls, processes, and oversight mechanisms that enable responsible and secure use of AI while supporting innovation. You will help create a scalable, risk-based approach for registering, evaluating, monitoring, and governing AI solutions, including internally developed, purchased, and vendor-embedded technologies.

Working closely with partners across technology, security, compliance, HR, and business teams, you will help establish governance practices that can be adopted across the organization. Because AI technologies and risks continue to evolve rapidly, this position requires ongoing learning, curiosity, and continuous refinement of governance processes and standards. The ideal candidate brings experience in AI engineering, software development, data engineering, or related disciplines, along with a collaborative, hands‑on approach to solving complex challenges and balancing innovation with risk management.

Some of the impactful contributions you'll make as MISO's AI Governance Engineer include:

• Owning the technical vision, architecture, and roadmap for the enterprise AI governance platform, building and operating it as a scalable internal product.
• Defining a repeatable, risk tiered governance framework (including measurement, evaluation, monitoring, and incident response) to ensure teams can apply the right controls to any AI solution.
• Delivering a central AI registry and intake process that identifies, registers, and tiers highrisk and high visibility AI systems across the enterprise.
• Building automated capabilities for registration, observability, and evidence capture, ensuring traceability across data, models, prompts, versions, and evaluations from deployment onward.
• Creating reusable evaluation tooling for ML, generative AI, and agentic systems, and validate that governance measures and model based evaluations are accurate and continuously improving.
• Defining monitoring thresholds, incident response protocols, and rollback runbooks for AI failure, degradation, or policy violations, validating them through exercises such as tabletop tests.
• Providing transparency to leadership through reporting on AI quality, usage, cost, and value, while collaborating with security, privacy, compliance, risk, and the AI Working Group to drive consistent governance adoption.

You'll need the following skills to be successful as AI Governance Engineer
:

• Bachelor's degree in Computer Science, Software Engineering, Data Science, Artificial Intelligence, or a related field; a master's degree, relevant certifications, or equivalent experience may also be considered.
• 8+ years of experience in software, data, or machine learning engineering, including at least 3 years building or evaluating production ML or AI solutions.
• Experience designing, building, and operating shared platforms or internal products used across multiple teams.
• Solid understanding of model training, evaluation, and failure modes, with the ability to design sound evaluation approaches.
• Hands‑on experience with AI‑assisted development tools.

Experience in two or more of the following:

• Evaluating or monitoring ML, generative AI, retrieval‑augmented, or agentic systems.
• Observability, telemetry, or alerting for production systems.
• Test automation or quality engineering for non‑deterministic systems.
• MLOps/LLMOps, including experiment tracking, versioning, and model or artifact registries.
• Data quality and validation practices for AI relevant datasets.
• Cloud cost management or usage analytics.

Preferred Experience:

• Master's…