Senior Applied AI Engineer

Puntt AI ·

senior

Salary Range (USD)

$185k - $210k

Location

San Francisco, USA

Visa Support

Not mentioned

Funding Stage

Unknown

Job Responsibilities

  • owns the agentic core
  • multi-agent orchestration
  • RAG and retrieval
  • stateful async workflows (Temporal)
  • eval frameworks that make compliance AI trustworthy at scale

Required Skills

production engineeringbuilding with LLMs in real applicationsstrong Pythonhands-on RAG

Engineering Culture & Tech Stack

PythonLLMsRAGTemporal
failure modes
observability
reliable

Raw Post

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Puntt AI | Forward Deployed Engineer + Senior Applied AI Engineer (Agentic Systems) | Onsite SF | Full-time Puntt AI is the system of record for enterprise marketing compliance. Our AI agents turn hours of manual brand and packaging review into minutes of automated precision. Danone, Nestlé, and Kenvue are live customers. The product works. Now we scale. Forward Deployed Engineer | $190k + equity https://wellfound.com/l/2CiVyv The FDE is the person in the room when an enterprise customer shows you their actual broken process. You run discovery, figure out what's really going wrong, configure and ship against it, and bring that signal back to product in a way the team can actually use. You work directly alongside our CEO in live enterprise cycles. What you learn shapes what we build next. Best fit: solutions engineering, field engineering, or technical founder background. You've been in enterprise rooms, you get to the real problem fast, and you can build the thing that proves the fix. Full stack, AI-native, 7+ years. Senior Applied AI Engineer | $185k-$210k + 0.75%-1.25% equity https://wellfound.com/l/2C3WzL This role owns the agentic core -- multi-agent orchestration, RAG and retrieval, stateful async workflows (Temporal), and the eval frameworks that make compliance AI trustworthy at scale. If you've spent real time thinking about failure modes, observability, and what reliable actually means when LLMs are in the loop, that's who we're looking for. 5-7+ years production engineering. 1-2+ years building with LLMs in real applications. Strong Python. Hands-on RAG.

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