We Are:
Accenture is a leading global professional services company that helps the world’s leading businesses, governments and other organizations build their digital core, optimize their operations, accelerate revenue growth and enhance citizen services—creating tangible value at speed and scale. We are a talent- and innovation-led company with approximately 790,000 people serving clients in more than 120 countries. Technology is at the core of change today, and we are one of the world’s leaders in helping drive that change, with strong ecosystem relationships. We combine our strength in technology and leadership in cloud, data and AI with unmatched industry experience, functional expertise and global delivery capability. Our broad range of services, solutions and assets across Strategy & Consulting, Technology, Operations, Industry X and Song, together with our culture of shared success and commitment to creating 360° value, enable us to help our clients reinvent and build trusted, lasting relationships. We measure our success by the 360° value we create for our clients, each other, our shareholders, partners and communities. Visit us at accenture.com.
Our AI and Data practice sits at the intersection of deep industry knowledge and applied AI and data engineering. We help the world’s leading Resources and Utilities organizations reinvent how they run — designing the data foundations, AI platforms, and governance models that turn data into trusted, production-grade intelligence. We are not looking for generalists who advise on AI in the abstract. We need practitioners who understand how enterprises actually operate, where the friction lives, and how to engineer smarter solutions using AI and data to fundamentally transform business processes and outcomes.
You Are:
You are a Senior AI engineering Leader who architects and delivers enterprise AI platforms spanning multiple model providers and cloud ecosystems. You set the technical standards for how generative and agentic AI is built, secured, and run at scale, and you lead multiple engineering teams to deliver on them. You are a credible technical authority on hyperscaler AI services, model selection, LLMOps, and enterprise-grade deployment.
The Work:
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.
Travel may be required for this role, varying from 0 to 100% depending on business need and client requirements.
Here’s What You Need:
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). If Associate’s Degree, must have equivalent minimum 6-year work experience
Bonus Points If
You have a Master’s degree in a relevant field
You have Cloud architecture or AI engineering certifications (AWS, Azure, or Google)
You have demonstrated thought leadership or published innovation work in enterprise AI
