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 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

Compensation at Accenture varies depending on a wide array of factors, which may include but are not limited to the specific office location, role, skill set, and level of experience. As required by local law, Accenture provides a reasonable range of compensation for roles that may be hired as set forth below.

We anticipate this job posting will be posted until 08/25/2026.

Accenture offers a market competitive suite of benefits including medical, dental, vision, life, and long-term disability coverage, a 401(k) plan, bonus opportunities, paid holidays, and paid time off.

See more information on our benefits here:

Role Location Annual Salary Range
California $70,350 to $205,800
Cleveland $59,100 to $164,600
Colorado $63,800 to $177,800
District of Columbia $68,000 to $189,300
Illinois $59,100 to $177,800
Maine $54,400 to $151,400
Maryland $63,800 to $177,800
Massachusetts $63,800 to $189,300
Minnesota $63,800 to $177,800
New York $66,300 to $205,800
New Jersey $68,000 to $205,800
Virginia $59,100 to $189,300
Washington $80,200 to $189,300