Staff Applied AI Engineer
$230k - $275kPeople In AI
Job Description
Staff Applied AI Engineer, Agents & Model Adaptation
\n \nCompensation: $230,000–$275,000 base + equity
\n \nLocation: New York City | 5 days onsite
\n \nCompany: Venture-backed AI startup building sophisticated, real-world AI systems.
\n \nThe Opportunity
\nPeople In AI is partnering with a fast-growing, venture-backed technology company developing advanced AI solutions for complex, data-intensive workflows. With strong commercial momentum and an experienced technical team, the business is investing heavily in its next generation of AI capabilities, with a particular focus on agentic systems, LLM fine-tuning, and model optimization.
\n \nThey're looking for a Staff Applied AI Engineer to take ownership of critical AI architecture and help build scalable, reliable, production-grade AI systems.
\n \nThe Role
\nYou'll lead the design, adaptation, evaluation, and deployment of LLM-powered systems, with a particular focus on production AI agents and specialized language models.
\n \nA major part of the role involves determining when to leverage frontier models versus fine-tuning and deploying smaller open-weight models, balancing quality, latency, reliability, and cost.
\n \nYou'll also develop robust agent architectures, establish evaluation frameworks, and build continuous improvement loops that turn real-world feedback into better-performing models.
\n \nThis is a hands-on Staff-level individual contributor role with significant technical ownership and architectural influence.
\n \nWhat You'll Do
\n- \n
- Own model selection and adaptation strategy across frontier and open-weight LLMs. \n
- Fine-tune and optimize language models using techniques such as LoRA, QLoRA, supervised fine-tuning, and preference optimization. \n
- Architect and build production-grade AI agents involving tool calling, orchestration, context management, and structured outputs. \n
- Develop feedback loops that transform production data and user interactions into training datasets and evaluation benchmarks. \n
- Build robust evaluation frameworks to measure model quality, hallucinations, accuracy, latency, and cost. \n
- Design and optimize model-serving infrastructure, including batching, quantization, and inference performance. \n
- Implement guardrails, observability, and safety measures to support reliable AI deployment. \n
- Provide technical leadership through architecture decisions, design reviews, and mentorship while remaining hands-on. \n
What You'll Bring
\n- \n
- Experience in software engineering, applied ML, or a related technical discipline. \n
- Proven experience designing and deploying ML or LLM systems in production. \n
- Hands-on experience fine-tuning LLMs , with a strong understanding of training techniques, evaluation, and performance trade-offs. \n
- Experience building production agentic AI systems that integrate external tools and structured outputs. \n
- Strong Python and PyTorch skills, alongside familiarity with modern LLM training frameworks. \n
- Practical experience with model evaluation, inference optimization, and production monitoring. \n
- Ability to balance model quality, infrastructure complexity, latency, and cost. \n
- Strong architectural judgment and the ability to influence technical direction at Staff level. \n
- A pragmatic, experimental mindset and an interest in solving challenging applied AI problems. \n
Why Join?
\n- \n
- Technical ownership: Set the direction for core AI systems and influence key architectural decisions from day one. \n
- Cutting-edge applied AI: Work across LLM fine-tuning, agentic systems, model optimization, and production infrastructure. \n
- Real-world impact: Build AI capabilities that solve meaningful problems and deliver measurable results. \n
- High-growth environment: Join a well-backed business with strong momentum and significant opportunities for personal and technical growth. \n
- Hands-on Staff leadership: Drive technical strategy, mentor talented engineers, and stay close to the code. \n
About People In AI
\nPeople In AI is a specialist recruitment partner connecting exceptional AI, machine learning, and engineering talent with ambitious companies building the next generation of intelligent technology. We work with innovative startups and established technology businesses to help talented engineers and AI specialists find opportunities where they can make a meaningful impact.
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