Fluxon

Chief Marketing Officer

• Shape our content and distribution strategy - what we say, where we show up, and who we need to reach to grow awareness and demand
• Set content priorities and rhythm, owning our editorial roadmap and aligning it with our business goals
• Define and evolve our brand voice and messaging so our marketing is clear, consistent, and easy to understand
• Lead content development cross-functionally, partnering with internal stakeholders and subject matter experts to turn ideas and expertise into compelling content
• Track what’s working (and what’s not) and use those insights to guide channel investment, content direction, and experimentation

Director of Marketing

Full-stack Engineer

• Design and implement end-to-end AI systems and their parts, including data ingestion, preprocessing, model inference, and output structuring
• Build and optimize RAG (Retrieval-Augmented Generation) systems and Agentic workflows using frameworks like LangChain, LangGraph, ADK (Agent Development Kit), Genkit
• Deploy models to production environments (AWS/GCP/Azure) using Docker and Kubernetes, ensuring high availability and scalability
• Implement feedback loops to evaluate model performance (accuracy, hallucinations, relevance) and set up monitoring for drift in production
• Work closely with other engineers to integrate AI endpoints into the core product and with product managers to define AI capabilities
• Fine-tune open-source models (e.g., Llama, Mistral) for specific domain tasks and optimize them for latency and cost

Senior Software Engineer

• As an AI Engineer at Fluxon, you’ll take the lead in designing, building and deploying AI-powered applications for our clients.
• Design and implement end-to-end AI systems and their parts, including data ingestion, preprocessing, model inference, and output structuring
• Build and optimize RAG (Retrieval-Augmented Generation) systems and Agentic workflows using frameworks like LangChain, LangGraph, ADK (Agent Development Kit), Genkit
• Deploy models to production environments (AWS/GCP/Azure) using Docker and Kubernetes, ensuring high availability and scalability
• Implement feedback loops to evaluate model performance (accuracy, hallucinations, relevance) and set up monitoring for drift in production
• Work closely with other engineers to integrate AI endpoints into the core product and with product managers to define AI capabilities
• Fine-tune open-source models (e.g., Llama, Mistral) for specific domain tasks and optimize them for latency and cost