pinpoint
AI Engineer
Kharon
Denver, USA
Full-time
Mid · 4+ years experience
Hybrid
USD 130000-170000 yearly / year
Discovered 1 weeks ago
PythonLangChainLangGraphPydanticSQLAlchemyAlembic
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PythonLangChainLangGraph
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PythonLangChainLangGraphPydanticSQLAlchemyAlembic
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RESPONSIBILITIES:
- Design, develop, and ship proof-of-concept AI applications within days or weeks. Work in fast, agile cycles to test ideas, gather feedback, and refine models and interfaces.
- Build and integrate advanced AI components, including Model Context Protocol clients and servers, foundation model fine-tuning, and multi-agent orchestration frameworks (eg. Claude Agent SDK, LangChain, AutoGPTI)
- Take features from idea to production, including architecting data flows, writing high-quality code, containerizing services, and deploying them in secure cloud environments (e.g., AWS).
- Partner closely with product managers, designers, engineers, and data scientists to translate abstract business problems into concrete, scalable AI systems.
- Develop production-grade data pipelines integrating data to/from AI systems.
- Develop and maintain internal tools to speed up development cycles, CI/CD scripts, evaluation harnesses, dashboards, and secure sandbox environments.
- Ensure AI systems are monitored, explainable, and aligned with ethical, regulatory, and performance standards.
- Stay at the forefront of AI/ML advancements, evaluate open-source frameworks, and share best practices across the team.
QUALIFICATIONS:
- Bachelor's or Master’s degree in Computer Science, Artificial Intelligence, Engineering, or a related field preferred.
- 4+ years of software engineering or machine learning experience, with a focus on applied AI.
- Strong software development skills in Python and experience with libraries like Langchain/Langgraph, Agent SDKs, Pydantic, SQLAlchemy/Alembic, PySpark/Polars/Pandas.
- Experience with tracing systems (MLFlow, Sentry), RAG Systems, Memory Systems, MCP Servers, Agent Skills, and knowledge of different models and tradeoffs.
- Strong understanding of how to make use of AI tools for rapid development (Cursor, Claude Code, etc)
- Familiarity with containerization (Docker), cloud deployment (AWS preferred, Github Actions)
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