
Intelligent Agent Developer for Sustainability Applications
1 day ago
Sustainability Data Engineer
Job DescriptionWe are seeking a skilled engineer to design, develop and deploy large language models for sustainability applications. The ideal candidate will have hands-on experience building with LLMs, GenAI frameworks or RAG systems, and proficiency in Python, Transformers and modern GenAI frameworks.
The primary focus of this role is to architect and scale intelligent agents that drive automated sustainability workflows across global supply chains and corporate operations.
Responsibilities:- Design, evaluate and ship agentic systems using real-world data.
- Develop and optimize retrieval-augmented generation (RAG) pipelines and multi-agent workflows using LangChain or LlamaIndex.
- Implement evaluation frameworks (OpenAI Evals, Ragas, TruLens) to measure agent performance, factuality and robustness.
- Fine-tune and serve LLMs (via LoRA/QLoRA) for sustainability-specific use cases, ensuring speed and relevance.
- Leverage vector databases (Weaviate, FAISS, Pinecone) for context injection and document grounding.
- Deploy inference stacks using vLLM, TGI, or Ollama; build modular, scalable agent architectures.
- Hands-on experience building with LLMs, GenAI frameworks or RAG systems — whether in a company, research project, or independent build.
- Proficiency in Python, Transformers (Hugging Face), and modern GenAI frameworks (LangChain, LlamaIndex).
- Demonstrated ability to design, evaluate and ship agentic systems using real-world data.
- Strong understanding of prompt engineering, context handling, and model evaluation.
- Exposure to MLOps workflows — model deployment, monitoring and lifecycle management.
- You will grow with our organization by working at the frontier of GenAI + Climate.
- You will be solving global-scale sustainability problems with real-time, intelligent systems.
- You will be working in a fast-moving, deeply collaborative team with design, engineering and domain depth.
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