Lead AI/LLM Engineer (Contract)

About the Opportunity:We’re partnering with a global energy industry leader to build an AI-driven intelligence platform that turns complexity into clarity — enabling organizations to understand change faster, act decisively, and unlock new levels of strategic advantage. This is a rare opportunity to work shoulder-to-shoulder with a global market leader, tackling high-impact problems with cutting-edge technology and taking bold ideas from 0 to 1. As the Lead LLM / AI Engineer, you’ll architect, build, and deploy the machine learning and LLM infrastructure that powers this new vertical SaaS product—from early experimentation through production-grade deployment. You’ll work closely with our product, data, and engineering teams to turn raw data into intelligence and prototypes into scalable systems. This is a hands-on technical lead role for someone who thrives at the intersection of AI research and applied product engineering. • • Please note this is a 12 month contract (1099). Extension possibility TBD. In This Role, You Will: • Design and implement the venture’s AI and LLM architecture, including model selection, fine-tuning, RAG pipelines, and production integration. • Develop and iterate on applied AI systems—from prototype agents and natural-language interfaces to predictive and optimization models in a small language model. • Build retrieval-augmented generation (RAG) pipelines leveraging structured and unstructured industry data (documents, telemetry, sensor data, etc.). • Evaluate and integrate LLM APIs and open-source frameworks (e.g., OpenAI, Anthropic, LangChain, LlamaIndex, Hugging Face) for use-case fit, cost, and performance. • Collaborate with product and design teams to translate complex technical possibilities into intuitive product experiences and user workflows. • Establish best practices for model evaluation, prompt engineering, and monitoring to ensure reliability, explainability, and business alignment. • Lead technical decisions and mentor junior engineers, helping to establish the AI engineering culture and development standards for the new venture. • Prototype rapidly, measure impact, and scale what works—balancing innovation with pragmatic delivery. What You Bring: • 6+ years of professional experience in applied machine learning, NLP, or AI engineering—ideally with exposure to enterprise or B2B SaaS environments. • Deep understanding of LLM architectures, fine-tuning, and retrieval-augmented generation (RAG). • Experience with vector databases, embeddings, and knowledge-graph construction. • Proficiency in Python and modern AI/ML frameworks (PyTorch, TensorFlow, Hugging Face, LangChain, LlamaIndex, etc.). • Strong engineering fundamentals—experience with cloud infrastructure (GCP, AWS, or Azure), CI/CD, and scalable microservices. • Comfort working in ambiguous, 0→1 environments, where you help shape both the product and the technical roadmap. • Excellent communication skills and the ability to collaborate with cross-functional teams—including product managers, designers, and domain experts.