Overview As Engineering Manager for AI Agents, you will lead the design and delivery of production-grade AI agents that scale across industries. You will start hands-on, then grow a team of engineers while maintaining high reliability and customer impact. You'll guide the full agent development lifecycle, from pilots to deployment and iteration, and partner with enterprises to solve real business challenges. This is a mission-critical role shaping Sierra's platform and its future in AI-enabled workflows.
Compensation / Benefits- Unlimited PTO
- Medical, dental, and vision benefits
- Life insurance and disability benefits
- Parental leave
- Fertility and family building benefits
- Equity participation
Responsibilities- Lead design and delivery of production-grade AI agents across industries
- Own the Agent Development Life Cycle from pilot to deployment and iteration
- Guide and coach engineers to achieve ADLC best practices and on-time delivery
- Collaborate with enterprises and startups to translate business needs into scalable AI solutions
- Shape the evolution of Sierra's core platform through customer-facing work and cross-functional collaboration
Key requirements- Experience building and scaling end-to-end production systems
- Strong technical problem-solving in ambiguous environments
- Hands-on leadership blending high standards with empathy
- Proven ability to translate business needs into technical deliverables
- Excellent communication across technical and non-technical audiences
- Degree in Computer Science or related field, or equivalent professional experience
- AI-related experience and production AI/LLM deployment a plus
- Familiarity with tools for AI agents: eval frameworks, agent tooling, RAG pipelines, prompt engineering
- Experience with React, TypeScript, and/or Go
- Experience interfacing with customers or leading technical projects with external stakeholders
- empathy in leadership
- customer-centric mindset
- clear communication
- AI agents development and deployment
- Agent tooling and eval frameworks
- RAG pipelines