Responsibilities
- Design and build AI applications using foundation models (Anthropic, Gemini, OpenAI) layered with internal data and context
- Build and maintain AI agents and automation workflows to improve access to insights and reduce manual work
- Write detailed instruction sets to guide agent behavior across various tasks
- Design interaction layers for agents, including UI/UX components, streaming responses, and human-in-the-loop control
- Build internal systems to evaluate agent performance, track reliability, and identify improvement opportunities
- Support internal teams in adopting and iterating AI tooling across workflows
Requirements
- 2+ years experience in software engineering with strong Python skills
- Experience building applications using LLMs via APIs or open-source frameworks such as LangChain
- Ability to move fast, adapt quickly and ship iterative value-driven solutions
- Comfortable working with data models, querying databases, and structuring input/output for AI systems
- Organized, good at prioritization, and capable of effectively managing multiple projects simultaneously
Nice to Have
- Experience with AI evaluation frameworks or measuring agent reliability
- Familiarity with building Slack bots, browser extensions, or internal integrations
Current Tech Stack
- AI Engineering: LangChain / LangGraph
- Observability: Datadog, LangSmith
- Backend: Python
- Data: BigQuery, dbt
- Infrastructure: GCP, LLM providers
- CI/CD & Infra: GitHub Actions, Terraform, ArgoCD
- Project Management: Linear, Notion
