Position: LangChain / LangGraph Developer
Location: Richmond, VA
Duration: Long term
Job Summary
We are seeking a skilled LangChain / LangGraph Developer to design, develop, and deploy advanced AI-powered applications using Large Language Models (LLMs).
The ideal candidate will have hands-on experience building agentic workflows, orchestrating multi-step reasoning pipelines, and integrating AI solutions into enterprise environments.
You will collaborate with data engineers, ML engineers, and product teams to create scalable, production-grade generative AI systems.
Key Responsibilities
Design and develop AI applications using LangChain and/or LangGraph frameworks.
Build and manage agent-based workflows, tool integrations, and memory architectures.
Integrate LLMs such as OpenAI, Anthropic, Azure OpenAI, or open-source models into enterprise applications.
Develop RAG (Retrieval-Augmented Generation) pipelines using vector databases like Pinecone, Weaviate, FAISS, or Chroma.
Optimize prompts, chains, and graphs for performance, cost, and accuracy.
Implement orchestration, state management, and error handling for complex AI workflows.
Collaborate with DevOps teams to deploy AI services on AWS, Azure, or Google Cloud Platform.
Ensure security, compliance, and responsible AI practices.
Monitor model performance and continuously improve system quality.
Stay updated with the latest advancements in Generative AI and agent frameworks.
Required Skills & Qualifications:
Bachelor s or Master s degree in Computer Science, AI, Data Science, or a related field.
Strong programming skills in Python.
Hands-on experience with LangChain and/or LangGraph in production or advanced POCs.
Solid understanding of LLMs, prompt engineering, embeddings, and vector search.
Experience building RAG pipelines and agentic architectures.
Familiarity with REST APIs, microservices, and database design.
Knowledge of Docker, Kubernetes, or CI/CD pipelines is a plus.
Strong problem-solving skills and ability to work in a fast-paced environment.
Preferred Qualifications:
Experience with multi-agent systems and workflow orchestration.
Exposure to fine-tuning, model evaluation, or guardrails frameworks.
Knowledge of Graph-based reasoning and stateful AI applications.
Prior experience developing enterprise AI chatbots, copilots, or automation tools.
Understanding of data privacy and AI governance.
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