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LangChain Developer

KDCI · Virtual Assistant Services · Business Process Outsourcing (BPO) · Python · 4 months ago

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Location

Remote (Philippines)

Seniority

Junior · 2+ years exp

Confirmed on the employer's own hiring board on Nov 3, 2026. First seen by Alion on Jul 20, 2026. KDCI scores C on the Alion truth index.

Overview

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Impact

Profile match

KDCI

KDCI, or Key Discovery Consulting, is an offshore staffing and outsourcing company that builds dedicated full-time remote teams in the Philippines for overseas clients, with its delivery center in Pasig and a US office in Carson, California. Founded in 2011 by executives with long outsourcing experience, it supplies staff for accounting, customer support, legal operations, creative production, engineering and AI work. Its openings, all based in Pasig, include accounting and accounts payable specialists, SaaS and customer support specialists, power systems engineers, CAD drafters, graphic and AI image designers, social media specialists and AI and automation engineers.

kdci.co · HQ: Pasig, Philippines · Virtual Assistant Services · Business Process Outsourcing (BPO) · 51-200 employees · Est. 2011

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

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

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