About the Role Were building the future of AI-powered Carbon Economy driving transparency, intelligence, and automation across the energy and carbon monitoring, measurement, modeling, and management. As a Full Stack Developer , you will be central to architecting scalable, production-grade software solutions that integrate Generative AI , retrieval pipelines , and agentic architectures to unlock new efficiencies and insights for energy and sustainability stakeholders. Youll work closely with product strategists, AI researchers, and blockchain engineers to deliver applications that are intuitive, intelligent, and mission-critical for the evolving carbon economy. Key Responsibilities Architect and develop full-stack platforms for the energy and carbon management domain combining real-time data, AI workflows, and smart analytics. Design and maintain performant, scalable front-end (React, Vue, or equivalent) and back-end (Python, Node.js, or Go) systems. Lead the integration of Generative AI capabilities using frameworks such as Langchain , LangGraph , LangTools , and Cursor . Build RAG (Retrieval-Augmented Generation) pipelines using vector databases (e.g., Pinecone, Weaviate, Chroma, FAISS) to enhance AI decision support. Implement Agentic AI architectures that allow for autonomous decision-making and multi-step reasoning. Collaborate with blockchain developers to bridge AI interfaces with carbon credit registries, exchanges, and digital asset systems. Deploy production-grade APIs and AI-driven interfaces that enhance transparency, pricing, and validation across carbon offset transactions. Work cross-functionally with sustainability experts and quant teams to translate market needs into usable, impactful applications. Contribute to system architecture, CI/CD, observability, and security compliance for AI-driven carbon platforms. Required Qualifications 3-4+ years of full stack development experience , with proven track record deploying customer-facing products in production. Proficiency with JavaScript/TypeScript , Python , and modern frameworks (React, FastAPI, Node.js). Hands-on experience embedding GenAI capabilities in real-world applications (e.g., GPT-4- powered agents, summarizers, auto-taggers). Strong understanding and implementation of RAG pipelines and vector database systems . Experience building autonomous agent workflows with tools like Langchain , LangGraph , or LangTools . Comfort with API-first architecture, microservices, and cloud deployments (AWS, GCP, or Azure). Familiarity with energy, carbon, or climate-tech ecosystems is a plus. Preferred Qualifications Experience working in energy trading , climate finance , or carbon markets . Experience with blockchain , smart contracts , token generation , or decentralized asset registries . Understanding of tokenized carbon credits or blockchain-based MRV (Monitoring, Reporting, Verification) solutions. Exposure to prompt engineering , embedding optimization , and AI observability. Background in ESG platforms, sustainability analytics, or digital MRV tools. Experience with geospatial data visualization or time-series forecasting in carbon and energy applications. Contributions to open-source AI or climate-tech communities.
We are building the future of staffing: humans and AI Agents working together. We are looking for an AI Engineer who can design, build, and deploy AI-powered Agents to automate tasks and collaborate with our Virtual Assistants (VAs) and clients. This role combines applied AI engineering, workflow automation, and hands-on development with cutting-edge technologies. Key Responsibilities: Work closely with VAs and client teams to identify automation opportunities in daily workflows. Design and develop AI Agents that automate tasks such as scheduling, research, reporting, email triage, and data entry. Implement Retrieval-Augmented Generation (RAG) pipelines, LLM-based workflows, and agent architectures. Deploy AI solutions into production environments with scalability and reliability in mind. Collaborate with internal and client teams on AI-driven projects, ensuring practical and measurable business impact. Continuously monitor, evaluate, and improve AI models, workflows, and automations. Tech Stack & Tools: Python (FastAPI, Flask), JavaScript (React/Node.js) Generative AI APIs (OpenAI, Anthropic, etc.) LangChain, LlamaIndex, CrewAI, Autogen Vector Databases (Pinecone, Weaviate, ChromaDB) Cloud (AWS, GCP, Azure) Automation frameworks & workflow orchestration tools Required Qualifications: Hands-on experience building with LLMs, RAG pipelines, or agent frameworks. Strong programming skills in Python; familiarity with JavaScript/TypeScript is a plus. Experience with APIs, databases, and cloud deployment. Understanding of prompt engineering and model fine-tuning. Ability to work collaboratively with cross-functional teams and non-technical stakeholders. Preferred Qualifications: Experience in workflow automation or business process automation. Familiarity with HRTech or staffing/outsourcing workflows. Exposure to Replit, GitHub Codespaces, or other cloud-based dev platforms.