Senior/Staff Applied AI Engineer
Storm2
New York, United States · Posted October 21, 2026
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Pay compared with the market
This listing does not state pay. Across 229 open senior listings that state pay, the middle half runs $180,000 to $250,000 and the median is $222,000.
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About the job
⚡ Staff Applied AI Engineer – LLMs & Agents
🌍 New York City, NY (In-office)
💲 $250k–$320k Base + Equity
The Company
Storm2’s client is a claims intelligence startup using AI and data to uncover fraud across property and casualty insurance. They’re solving a difficult problem where the data is messy, fraudsters adapt, and false positives have real consequences.
The Role
Frontier models work, but they’re expensive and slow at scale. Smaller open-weight models solve that problem, but only if you can preserve the reasoning quality.
That trade-off is the job.
You’ll own which models the company builds on, fine-tune open-weight LLMs for specific workflows, put them inside production agents, and build the evals that decide what actually ships. This is a Staff IC role with genuine architectural ownership, while staying hands-on in Python and PyTorch.
What you’ll be working on:
Fine-tuning open-weight LLMs with LoRA, QLoRA, SFT and DPO.
Building production agents with tool use, structured outputs and guardrails.
Turning real investigator feedback and agent traces into training data.
Benchmarking models on accuracy, hallucinations, false positives, latency and cost.
Serving and optimising models through vLLM, TGI, Triton or similar.
Setting the technical direction for applied AI across the business.
You’ll be good here if:
You’ve actually fine-tuned LLMs and can explain what moved the numbers.
You’ve shipped agents into production, not just built demos.
You’re strong in Python, PyTorch and the Hugging Face ecosystem.
You’ve made real trade-offs between model quality, latency and cost.
You enjoy problems where the ground truth is messy and the answer isn’t sitting neatly in a research paper.
Experience with quantisation, distillation, entity resolution, graph ML or highly imbalanced detection is a big plus.
Why apply?
You won’t be building another wrapper around a frontier API. You’ll decide which models run which workflows, how they’re trained, and whether they’re good enough to replace much larger models at production scale .
At $250k–$320k base + equity , they’re paying for someone who can make those calls and then build the systems themselves.
📧 Click ‘Easy Apply’ or email ben.watts@storm2.com
⚡ Storm2 is a specialist FinTech recruitment firm with clients across North America. Visit storm2.com or follow us on LinkedIn for the latest roles and intel.