Senior Artificial Intelligence Engineer, Honeycomb

• GenAI & LLMs: 5+ years of software engineering experience, with at least 2 years of experience building and shipping production-ready ML/AI-powered features
• Machine Learning: Expertise in modern AI/ML tools and concepts, particularly large language models, prompt engineering, retrieval-augmented generation, and evaluation techniques
• Backend Development: Proficiency in languages like Python, Go, or TypeScript
• Production Experience: Proven track record of owning and operating models and services in production environments
• Cross-Functional Skills: Effective collaboration with PMs, designers, and engineers in a product-focused environment
• Mentorship & Leadership: Experience mentoring engineers and influencing best practices within and beyond your immediate team
• Are excited to own business-critical projects end to end
• Thrive in ambiguous, fast-moving environments
• Care about building real value for users—not just optimizing metrics
• Want to mentor others while continuing to grow yourself

Desirable

• As a Senior AI Engineer II, you’ll lead high-impact projects, mentor teammates, and help define what great AI at Honeycomb looks like
• Lead projects implementing AI-powered product features from experimentation through production
• Improve the quality and reliability of our AI systems through prompt design, evaluation frameworks, and model tuning
• Influence architectural decisions across our ML/AI stack, tooling, and infrastructure
• Partner with Product, Design, and Engineering leaders to define and scope AI-driven product experiences
• Support non-AI engineering teams in integrating AI into their product areas—without creating knowledge silos
• Define and share best practices for integrating LLMs responsibly and effectively
• Shape evaluation and experimentation methodologies to support fast, iterative learning
• Mentor engineers on the use of AI/ML and prompt-based systems
• Gain deep knowledge of our core product workflows and the problems our users face
• Embrace our culture of experimentation, where short feedback loops and impact over perfection guide our work
• Level up the team’s skills through your expertise in LLMs, prompt engineering, and evaluation strategies
• Act as a multiplier by coaching others and shaping early best practices for safe and responsible AI development
• Partner across teams to scale AI adoption thoughtfully and effectively
• Help build and maintain shared AI infrastructure that empowers the entire engineering org to experiment and deliver
• Deliver AI-powered features that differentiate Honeycomb in a competitive market
• Contribute to our public story and strategy in the AI space