Hybrid Senior Lead – AI Engineering, LangGraph, Haystack, RAG Systems

Posted 2 weeks ago

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About the role

  • Architect & Lead: Design and oversee RAG pipelines using LangGraph, Haystack, LangChain, and OpenAI APIs for NeIO applications.
  • Mentor & Guide: Manage a team of 3–5 AI engineers; perform code reviews, pair programming, and architecture reviews.
  • Build & Integrate: Develop FastAPI-based microservices and vectorized retrieval layers (Qdrant, FAISS, Pinecone).
  • Optimize & Scale: Tune embedding quality, latency, and retrieval precision across multi-tenant data lakes.
  • Collaborate with Data & GIS Teams: Integrate structured and spatial data using PostGIS, QGIS, GeoPandas.
  • Implement Governance: Establish model observability, explainability metrics, and audit trails.
  • Drive Delivery: Translate business workflows (e.g., LeaseOps, Recon) into AI automation pipelines with measurable ROI.
  • Evangelize Open Source AI: Advocate for enterprise-grade, open-source-first design principles.

Requirements

  • Experience: 8–12 Years
  • AI / NLP: Hugging Face Transformers, spaCy, Haystack, OpenAI APIs
  • RAG / Agents: LangGraph, LangChain, retrieval orchestration, context window optimization
  • Vector Databases: Qdrant, FAISS, Pinecone, or Weaviate
  • Backend Engineering: FastAPI, RESTful API design, async Python
  • Data Processing: Pandas, DuckDB, PySpark, Airbyte (preferred)
  • Geospatial (Bonus): QGIS, PostGIS, GeoPandas
  • MLOps (Preferred): MLflow, DVC, Docker, Kubernetes
  • Version Control: Git, GitHub Actions, CI/CD automation

Benefits

  • Competitive compensation with performance-linked RSUs
  • Flexible, innovation-driven environment with direct impact on product evolution

Job title

Senior Lead – AI Engineering, LangGraph, Haystack, RAG Systems

Job type

Experience level

Senior

Salary

Not specified

Degree requirement

Bachelor's Degree

Location requirements

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