Applied AI Engineer

Rheaction • San Francisco, CA

35d • Onsite

About The Position

We're looking for an exceptional Applied AI Engineer to own and evolve production AI systems used by real customers. This is a hands-on role for an engineer who knows how to take modern AI models beyond prototypes and turn them into reliable, scalable production products. You'll work across model selection, fine-tuning, evaluations, AI infrastructure, and product development. The ideal candidate combines strong AI fundamentals with excellent software engineering and product instincts, with the opportunity to grow into a broader AI leadership role.

Requirements

• 4–8 years of applied AI, ML, or software engineering experience.
• Track record of deploying production AI systems that real users depend on.
• Strong Python and experience with PyTorch or TensorFlow.
• Hands-on experience with LLMs, fine-tuning, evaluations, and model selection.
• Experience with LLM orchestration frameworks such as LangChain, LlamaIndex, DSPy, Instructor, or similar.
• Strong software engineering and systems-design fundamentals.
• Product mindset and ability to turn business requirements into practical AI solutions.
• Strong ownership, communication, and ability to operate in a fast-moving startup.
• Able to work in person in San Francisco.

Nice To Haves

• AI agent or conversational AI experience.
• Voice AI, telephony, or real-time AI systems.
• RLHF / RLAIF experience.
• Experience building AI evaluation infrastructure or feedback loops.
• Experience with AI systems in regulated or compliance-heavy industries.
• Founding engineer or early-stage startup experience.
• Open-source AI projects, technical writing, or other independently shipped work.

Responsibilities

• Build, deploy, and continuously improve production LLM-powered applications.
• Evaluate and select models based on performance, cost, latency, and product requirements.
• Fine-tune models using proprietary datasets.
• Build robust evaluation frameworks to measure and improve AI performance.
• Design prompting and orchestration strategies for production AI agents.
• Develop feedback loops that allow AI systems to improve from real-world interactions.
• Build scalable AI workflows, APIs, and data pipelines.
• Monitor model performance and run experiments against defined quality metrics.
• Partner closely with product and engineering teams to translate business problems into AI solutions.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed