Himalayas · Partner listingLangChain Developer
KDCI
⌖ WorldwideSalary not providedRemoteNot specified · Full-time
Source: Himalayas ↗
Location & working arrangementWorking arrangement is supplied by the provider. Check the original advert for attendance and travel requirements.
Provider location / applicant eligibility: Worldwide
About the role
Role Summary
KDCI Outsourcing is looking for a LangChain Developer to build LLM-powered applications using the LangChain framework. You'll design chains, agents, and retrieval pipelines that power intelligent product features.
Key Responsibilities
Design and build applications using the LangChain (or LangGraph) framework
Develop chains, agents, and tool integrations for LLM-powered workflows
Build retrieval-augmented generation (RAG) pipelines with vector databases
Test and optimize prompt chains for accuracy and performance
Integrate LangChain applications with back-end systems and APIs
Stay current with updates to the LangChain ecosystem
Requirements
Requirements
2+ years of experience in software development, with hands-on LangChain experience
Strong Python skills
Experience with LLM APIs (OpenAI, Anthropic, or open-source models)
Familiarity with vector databases (Pinecone, Weaviate, Chroma, etc.)
Understanding of prompt engineering and RAG architecture
Nice-to-Haves
Experience with LangGraph or multi-agent orchestration
Familiarity with LlamaIndex or similar frameworks
Background in NLP or conversational AI
Highlights
Build LLM-powered apps using LangChain, RAG, vector databases, and AI agent workflows.
Originally posted on Himalayas
Skills mentioned in the listing
PythonNatural language processing
Recognised skills are extracted from the supplied description using canonical names and aliases. They are mentions, not verified essential requirements. Check the source advert for the employer’s full requirements and location restrictions.
Why these skills appear
Python · requirement-context
experience in software development, with hands-on LangChain experience Strong Python skills Experience with LLM APIs (OpenAI, Anthropic, or open-source models) Familiarity with vector databases (Pinecone, Weaviate,
Natural language processing · mentioned
chestration Familiarity with LlamaIndex or similar frameworks Background in NLP or conversational AI Highlights Build LLM-powered apps using LangChain, RAG, vector databases, and AI agent workflows. Originally post