Staff Software Engineer
Summary
Hands-on technical lead role at a venture-backed AI startup building AI agents for complex, data-intensive investigations: owning LLM fine-tuning (LoRA, QLoRA, SFT), agent architecture, evaluation frameworks, and inference/serving optimization. Onsite in NYC, Python/PyTorch stack, $235k–$285k base plus equity.
Staff Software Engineer
$235,000–$285,000 base + equity
New York City (onsite)
We're partnering with a fast-growing, venture-backed AI startup building intelligent systems to transform complex, data-intensive investigations.
With strong commercial traction, growing enterprise adoption, and significant technical challenges ahead, the company is looking for a Staff Software Engineer to lead the development of production AI agents and model adaptation systems.
This is a hands-on technical leadership role with ownership across LLM fine-tuning, agent architecture, evaluation, and inference infrastructure.
What You'll Do
- Own model strategy, balancing frontier and open-weight LLMs across accuracy, latency, and cost.
- Fine-tune and adapt open-weight models using LoRA, QLoRA, SFT, and preference optimization.
- Design and deploy production AI agents with tool use, orchestration, and structured outputs.
- Build evaluation frameworks to measure model performance, reliability, and hallucinations.
- Turn real-world user feedback and production traces into training data and continuous model improvements.
- Optimize model serving, inference performance, batching, and quantization.
- Drive technical architecture, mentor engineers, and remain hands-on in code.
What You'll Bring
- Strong background in applied AI, machine learning, or software engineering.
- Proven experience fine-tuning LLMs and deploying adapted models in production.
- Experience building production-grade AI agents and evaluation pipelines.
- Strong Python and PyTorch skills.
- Familiarity with Hugging Face, DeepSpeed, Ray, or similar frameworks.
- Understanding of LLM inference, model serving, observability, and cost optimization.
- Ability to lead technical decisions and solve ambiguous engineering challenges.
Tech Stack
- Python, PyTorch
- Hugging Face, DeepSpeed, Ray
- LoRA, QLoRA, SFT, preference optimization
- LLM agents, tool calling, orchestration
- Model serving, quantization, inference optimization
- LLM evaluation, observability, and guardrails
Why Join?
- Own the technical direction of AI agents and model adaptation at a growing startup.
- Work on challenging, real-world AI problems with proprietary data and direct customer feedback.
- Build and deploy sophisticated AI systems beyond proof-of-concept.
- Join a venture-backed, high-performing engineering team with strong commercial momentum.
- Receive meaningful equity and have a direct impact on product and company growth.
About People In AI
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