Principal Applied AI Scientist

We are looking for a Principal Applied AI Scientist to lead the design and deployment of cutting-edge Generative AI and LLM-powered systems for real-world, high-impact applications. 

This is a senior, hands-on leadership role for someone who can operate across the full stack of modern AI — from research and modeling to production systems and productization — while leading teams and defining technical direction. 

You will work at the intersection of LLMs, agentic systems, retrieval architectures, and large-scale AI platforms, building systems that move beyond prototypes into robust, production-grade intelligence systems. 

What You’ll Do 

• Lead the end-to-end design and development of large-scale AI/ML and Generative AI systems  
• Architect and deploy LLM-powered applications, including RAG pipelines and multi-agent systems  
• Drive the technical vision and roadmap for applied AI across the company  
• Build and lead a high-performing team of scientists and engineers  
• Design scalable retrieval and embedding systems powering intelligent applications  
• Develop agentic AI systems with tool use, memory, and reasoning capabilities  
• Own model lifecycle: data curation → training/fine-tuning → evaluation → deployment → monitoring  
• Partner with product, engineering, and executive leadership to translate business problems into AI solutions  

Required Qualifications 

• 7+ years of experience in Applied AI / Machine Learning / Generative AI
• M.S. in Computer Science, AI, Machine Learning, or a related field. PhD preferred.  
• Proven experience building and deploying production-grade AI systems at scale  
• Demonstrated leadership managing large cross-functional teams  
• Strong experience engaging with executives and product stakeholders 
• Deep expertise in LLMs, RAG, and agentic AI systems at scale  
• Strong system design skills across data, models, and infrastructure  
• Ability to move from research ideas → production systems → business impact  
• Strong ownership mindset with the ability to operate in fast-moving startup environments  
• Experience with multi-agent orchestration frameworks and tool ecosystems  

Preferred Qualifications

• Experience applying AI in cybersecurity, enterprise SaaS, or data-intensive domains  
• Background in search or large-scale retrieval systems  

Core Technical Expertise 

• Large Language Models & GenAI 
• RAG, Retrieval & Vector Systems 
• Fine-Tuning & Model Adaptation 
• Agentic AI Systems 
• Prompt Engineering & Optimization 
• Evaluation & Quality 
• Inference & Serving 
• Data Engineering & Synthetic Data 
• Multimodal AI 
• LLMOps & Observability 
• Platforms & Infrastructure

Individual pay reflects job-related skills, experience, and relevant education or training. Alongside base salary, this role includes equity, medical, dental and vision coverage, 401(k), and more.