Applied AI Engineer
Skills
- Hands-on experience with LLM APIs (OpenAI, Anthropic, etc.)
- Prompt engineering and RAG (retrieval-augmented generation) pipelines
- Multi-agent / agentic workflow frameworks (LangChain, LlamaIndex, etc.)
- Low/no-code orchestration platforms (n8n, Make, Zapier)
- Python and TypeScript/Node.js proficiency
- Familiarity with PostgreSQL and cloud deployment (AWS, Vercel, or similar)
- Experience with vector databases and embedding pipelines
- Evaluation frameworks for LLM outputs and monitoring production performance
- Ability to prototype quickly and rebuild properly when required
Responsibilities
- Own AI discovery, strategy, and a prioritized backlog of AI opportunities across the business.
- Define AI initiatives end-to-end: problem framing, data needs, build vs. buy, and success metrics.
- Build, integrate, and maintain AI-powered features using LLM APIs, RAG pipelines, and agentic frameworks.
- Rapidly prototype and deliver automation using low/no-code orchestration tools (n8n, Make).
- Integrate AI capabilities into existing systems in partnership with product and engineering.
- Own the full AI development lifecycle: prototyping, evaluation, deployment, monitoring, and iteration.
- Socialize AI capabilities, limitations, and roadmap across the organization as a subject-matter resource.
- Document implementations and transfer knowledge so teams can support and extend AI solutions.
Education
- Bachelor's degree in Computer Science, Engineering, or related field preferred
- Equivalent practical experience in software engineering and AI accepted
Benefits
- Fully remote, remote-first culture
- Monthly cell and internet stipend
- Access to WeWork locations
- Premium healthcare eligible from day one
- Flexible PTO and generous parental leave
- Inclusive, transparent OneTeam culture
- Reasonable accommodations for candidates with disabilities
Average salary estimate
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