What you will do
- Design and deploy end-to-end agentic pipelines for structured and unstructured energy data;
- Build and fine-tune LLM applications using RAG, vector databases, and knowledge graphs;
- Develop models for contract intelligence, price forecasting, and energy portfolio optimization;
- Deliver scalable APIs and AI services using FastAPI, Flask, or similar frameworks;
- Integrate with cloud-native platforms (AWS, GCP) and modern data infrastructure;
- Mentor peers and contribute to best practices in applied AI and ML engineering;
Must haves
- 7+ years of professional software development experience;
- 5+ years deploying machine learning systems in production;
- 3+ years building with LLMs, both locally-hosted and API-based (OpenAI, Gemini, etc.);
- Expertise in Python and libraries like PyTorch, TensorFlow, and Hugging Face;
- Hands-on experience with agentic pipelines, RAG, vector search, and prompt engineering;
- Deep familiarity with cloud platforms (AWS, GCP, Azure) and tools like Docker, Kubernetes;
- Experience designing scalable microservices and REST APIs for AI inference workflows;
- Excellent verbal and written communication — you’ll regularly present to the C-suite;
- Systems-level thinking with a product mindset;
- Upper-Intermediate English level.
Nice to haves
- Experience in an early-stage startup environment;
- Experience in energy, sustainability, or infrastructure tech;
- A commitment to ethical, socially responsible AI;
- Online thought-leadership, contributions to open-source AI/ML projects and research.
AgileEngine is an Inc. 5000 company that creates award-winning software for Fortune 500 brands and trailblazing startups across 17+ industries. We rank among the leaders in areas like application development and AI/ML, and our people-first culture has earned us multiple Best Place to Work awards.
If you're looking for a place to grow, make an impact, and work with people who care, we'd love to meet you! :)
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