AI Engineering Consultant - Utilities
About The Position
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.
Requirements
- 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
Nice To Haves
- Master’s degree in a relevant field
- Cloud or AI engineering certifications (AWS, Azure, or Google)
- Experience with agentic AI patterns and multi-agent orchestration
Responsibilities
- 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.
Benefits
- medical, dental, vision, life, and long-term disability coverage
- a 401(k) plan
- bonus opportunities
- paid holidays
- paid time off
Stand Out From the Crowd
Upload your resume and get instant feedback on how well it matches this job.
What This Job Offers
Job Type
Full-time
Career Level
Mid Level
