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  

• 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