Staff AI Engineer
Slang
What success looks like
- Lead the development and optimization of our conversational AI systems, working closely with conversation designers to implement solutions that address user pain points and enhance customer experience
- Design, implement, and maintain AI agent workflows using modern machine learning techniques and best practices
- Drive technical excellence by mentoring team members on AI engineering best practices and keeping the team updated on relevant industry developments
- Conduct and analyze A/B/N tests, or use causal methodologies to validate changes and improvements to our AI systems
- Evaluate and implement tools and systems for monitoring AI performance and detecting issues in production
- Collaborate with cross-functional teams to define and implement new features and capabilities
- Stay current with the latest developments in AI/ML, particularly in areas relevant to conversational AI and large language models
Key outcomes
- Continuously enhance our conversational AI platform’s capabilities.
- Achieve measurable improvements in guest satisfaction and conversation completion rates
- Maintain robust monitoring and optimization frameworks for AI system performance
- Enable engineers to independently develop and deploy LLM-based solutions
- Create practical training programs and documentation for AI/ML best practices
- Demonstrate team's increased velocity and confidence in shipping AI features
What you will bring
- You have at least 7+ years in software engineering, 5+ (inclusive is fine) in ML domain, 2+ with LLMs
- BS/MS in computer Science or related field
- Experience shipping production conversational AI systems
- Have shipped products with LLMs in production and seen issues with guardrails, performance and cost
- Have used methods for validating success like A/B/N testing and/or causal inference
- Ability to think strategically and creatively about product, tech debt, and performance / complexity / cost trade-offs
- Excellent communication skills, especially with non-technical stakeholders
- A desire to mentor engineers
- Pro-activity and ability to not only build end-to-end solutions yourself, but also lead a team to do so
- Experience with voice/telephone AI systems
- Background in restaurant/hospitality tech
- Track record of building and leading engineering teams
- Published research or contributions to AI/ML community