AI Engineering & Platform Leadership Senior Manager - Utilities

About the role

We are seeking a Senior AI Engineering Leader to architect and deliver enterprise AI platforms spanning multiple model providers and cloud ecosystems. This role involves setting technical standards, leading engineering teams, and shaping solutions for major AI programs.

Responsibilities

• Architect enterprise AI platforms - lead the architecture and delivery of enterprise AI platforms spanning multiple model providers (OpenAI, Anthropic) and cloud ecosystems (AWS, Azure, Google).
• Set technical standards - define reference architectures and technical standards for LLMOps, security, reliability, and cost governance across the AI estate.
• Lead engineering teams at scale - oversee multiple engineering teams delivering AI solutions at scale, providing technical direction, coaching, and quality assurance.
• Own model strategy - serve as senior technical authority on hyperscaler AI services and model selection, guiding enterprise-grade deployment of generative and agentic AI.
• Drive cost and security governance - establish FinOps-for-AI cost optimization practices and embed AI security and governance into platform design.
• Shape solutions and growth - partner with clients and pursuit teams to shape solutions, architectures, and delivery models for major AI programs.

Requirements

• Minimum of 10 years of experience in software or AI/ML engineering, including architecture leadership.
• Minimum of 6 years of experience architecting and delivering enterprise AI/LLM platforms across major cloud and model providers.
• Minimum of 3 years of experience with LLMOps/MLOps at scale and multi-cloud architecture (AWS, Azure, Google).
• Minimum of 5 years of experience leading engineering teams and end-to-end solution delivery.
• Minimum of 3 years of experience with AI security, governance, and cost optimization (FinOps for AI).
• Minimum of 1 year of experience serving utilities clients (electric, gas, or water) or in a utilities finance, controllership, or regulatory function.
• Bachelor's degree or equivalent (minimum 12 years' work experience).

Qualifications

• If Associate’s Degree, must have equivalent minimum 6-year work experience.
• Master’s degree in a relevant field preferred.
• Cloud architecture or AI engineering certifications (AWS, Azure, or Google) preferred.
• Demonstrated thought leadership or published innovation work in enterprise AI preferred.

Skills

• Strong understanding of AI and machine learning principles.
• Experience with multiple model providers and cloud ecosystems.
• Leadership experience in managing engineering teams.
• Expertise in LLMOps/MLOps at scale.
• Knowledge of enterprise-grade deployment of generative and agentic AI.
• Experience with AI security and governance.
• Ability to manage cost optimization practices.
• Strong communication and collaboration skills.

Benefits

• Market competitive suite of benefits including medical, dental, vision, life, and long-term disability coverage.
• 401(k) plan.
• Bonus opportunities.
• Paid holidays.
• Paid time off.

Pay

Annual salary range: $132,500 to $338,300.

Schedule

Travel may be required for this role, varying from 0 to 100% depending on business need and client requirements.