AI Engineering Consultant - Utilities

AI Engineer

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 791,000 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. 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 an AI Engineer who builds and integrates AI applications using leading model providers and cloud platforms. You develop LLM-powered applications, APIs, and pipelines—implementing RAG, prompt orchestration, evaluation, and guardrails—and you deploy and operationalize AI workloads on cloud infrastructure with scalability, security, cost efficiency, and reliability in mind. The Work: Build AI applications—develop and integrate AI applications using leading model providers (OpenAI, Anthropic) and cloud platforms (AWS Bedrock, Azure OpenAI, Google Vertex AI). Implement LLM patterns—implement RAG, prompt orchestration, evaluation, and guardrails in LLM-powered applications, APIs, and pipelines. Deploy AI workloads—deploy and operationalize AI workloads on cloud infrastructure with scalability, security, cost efficiency, and reliability in mind. Engineer with modern tooling—use Python, API integration, vector databases, and orchestration frameworks (e.g., LangChain, LlamaIndex) to build production-ready solutions. Apply DevOps practices—apply containerization (Docker/Kubernetes), CI/CD, and cloud security best practices across the AI delivery lifecycle. Travel may be required for this role, varying from 0 to 80% depending on business need and client requirements. Here's What You Need: Minimum of 3 years of experience in software or AI/ML engineering Minimum of 2 years of hands-on experience building AI applications with providers such as OpenAI, Anthropic, AWS Bedrock, Azure OpenAI, or Google Vertex AI Minimum of 2 years of experience with Python and API integration Minimum of 2 years of experience with RAG, vector databases, and orchestration frameworks (e.g., LangChain, LlamaIndex) Minimum of 1 year of experience with containerization (Docker/Kubernetes), CI/CD, and cloud security 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 or AI engineering certifications (AWS, Azure, or Google) You have experience with agentic AI patterns and multi-agent orchestration