Note: The job is a remote job and is open to candidates in USA. Marathon TS is seeking a founding AI Product Engineer to help shape their client’s product from the ground up. This role involves owning AI powered features, defining product requirements, and building across the full stack while iterating based on user feedback.

Responsibilities

• Own AI powered features end to end – from identifying user problems to shipping polished, production ready experiences
• Talk to users, define product requirements, and decide what's worth building next
• Design intuitive UX flows and interfaces for AI native interactions
• Build across the full stack – backend services, AI/LLM integrations, and frontend UI
• Develop and refine prompts, retrieval pipelines, and agentic workflows using frontier LLMs (Claude, Gemini, GPT)
• Build evaluation frameworks to measure model quality, accuracy, caching, fallback strategies, and cost optimization
• Help shape engineering culture, technical standards, and product direction as the team grows
• Stay current with advances in LLMs, RAG, agents, and evaluation techniques; bring promising ideas into the product
• Move fast, ship often, and iterate relentlessly based on user feedback

Skills

• 4+ years of professional software engineering experience
• Strong proficiency in Python and a modern web framework (FastAPI, Flask, Django, or similar)
• Frontend experience with React, TypeScript, or a comparable framework
• Hands on experience building applications with LLM APIs (OpenAI, Anthropic, Google, or open-source models)
• Solid understanding of prompt engineering, retrieval-augmented generation (RAG), and evaluation methods
• Strong product instincts – able to identify what's worth building and make sound UX decisions
• High autonomy – thrives without a detailed spec or established process
• Bias toward shipping; comfortable trading polish for speed when it matters
• Prior founding engineer, solo builder, or early-stage startup experience
• Design fluency (Figma, prototyping, visual design fundamentals)
• Experience with agent frameworks, tool use, or multi-step LLM workflows
• Familiarity with cloud platforms (GCP, AWS, or Azure) and containerized deployments
• Background in regulated or compliance-heavy domains (FedRAMP, HIPAA, SOC 2, etc.)

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