Senior Computer Scientist

What you'll do

• Define the architecture for agent learning systems to evaluate outcomes and capture quality signals for continuous improvement.
• Design evaluation pipelines that translate feedback into specific updates for prompts, skills, routing, and reward data.
• Apply machine learning techniques including preference learning, reward modeling, and reinforcement learning to production systems.
• Establish technical standards and direction through architecture reviews, design documents, and build-versus-buy evaluations.
• Develop prototypes and proof-of-concepts using current AI models, agent frameworks, and training methodologies.
• Evaluate third-party technologies based on their ability to deliver reliable and scalable production capabilities.
• Mentor engineers through code reviews, technical documentation, and architectural guidance.
• Translate business goals into a clear technical roadmap in collaboration with product and engineering stakeholders.

What we're looking for

• 12+ years of software engineering experience is required.
• Experience designing and architecting AI, ML, or data-intensive systems at scale is required.
• Experience crafting and delivering LLM and agentic systems including tool use and state management is required.
• Experience with reinforcement learning, preference learning, RLHF, or reward modeling in production systems is required.
• Experience designing evaluation and learning systems that connect agent actions to measurable outcomes is required.
• Demonstrated ability to translate ambiguous business or technical objectives into clear architecture and execution plans is required.
• Proficiency in Python and at least one additional programming language is required.
• Experience with cloud platforms like AWS or Azure, data pipelines, and ML infrastructure is required.