Design and build an agentic AI platform to manage renewable energy certificates and automate related workflows. Collaborate across teams to integrate the platform, optimize user onboarding, and iterate based on feedback and metrics.
About the role
- AI Engineer designing and building agentic systems for audit workflows. Collaborating closely with product and design teams in a hybrid work environment.
Responsibilities
- Design, build, and ship agentic systems that automate and augment complex audit workflows
- Translate customer problems into concrete agent behaviors and workflows
- Integrate and orchestrate LLMs, tools, retrieval systems, and logic into cohesive, reliable agent experiences
- Own agents in production, including performance and observability
- Use AI as core leverage in how you design, build, test, and iterate
- Prototype quickly to resolve uncertainty, then harden systems for enterprise-grade reliability
- Build evaluations, feedback mechanisms, and guardrails so agents improve over time
- Design prompts, retrieval pipelines, and agent orchestration systems that perform reliably at scale
- Make tradeoffs about what to build, what to cut, and what not to build at all
- Partner closely with Product and Design to define agent capabilities that drive real customer outcomes
- Stay deeply connected to how customers actually use agents and optimize for the highest impact problems
- Identify the highest-leverage capability gaps and unblock them without waiting for direction
- Take full ownership of large product areas rather than executing on narrow tasks
- Identify bottlenecks and unblock progress without waiting for direction
- Increase team velocity by building reusable abstractions, tools, and patterns for agent development
Requirements
- Multiple years of experience shipping production software in complex, real-world systems
- Experience with TypeScript, React, Python, and Postgres
- Built and deployed LLM-powered features serving production traffic
- Designed retrieval pipelines and agent orchestration systems
- Implemented evaluation frameworks for model outputs and agent behaviors
- Worked with vector databases, embedding models, and RAG architectures
- Hands-on experience with modern LLM APIs (OpenAI, Gemini, Anthropic, etc.) and agent frameworks
- Comfort operating in ambiguity and taking responsibility for outcomes
- Deep empathy for professional-grade, mission-critical software (experience with audit and accounting workflows are not required)
Benefits
- Competitive compensation packages with equity ownership
- Comprehensive health and wellness benefits
- Flexible time off and work schedules
- Technology reimbursements
- 401(k) plan
- Twice-yearly in-person offsites across the U.S.
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