Hire the Best LangGraph Specialists

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Yasser A.

Ismailia, Egypt

$25/hr
4.9
38 jobs

AI engineer. 30 jobs done on Upwork, $10K+ earned, 100% job success rate. What I mostly work on: โ†’ Agent systems. LangGraph, custom orchestration, MCP. Used for things like document analysis pipelines and internal company tools. โ†’ RAG. Pinecone or pgvector setups. Tuned for production, not just plug-and-play LangChain. โ†’ Full AI products. I've shipped paid marketplace apps and multi-agent backends. Real shipped products, not demos. Some recent work I'm proud of: Column Mate. A paid Monday marketplace app I built. Live on the Monday App Store (App ID 10601212). Pricing tiers from $0 to $300 a month. It has 4 features the leading competitor doesn't have, including the only AI Parse Updates feature on the whole marketplace. Auto Blog Automation. An n8n pipeline I built for a client. Cut their article production from about 4 hours per article to under 5 minutes. Publishes to 5 platforms automatically. Business Control Center. I migrated a flat-file JSON system to Postgres for a client. 9 migrations shipped. Dashboard reads under 100ms p95. My main stack: Python, Node.js, FastAPI, PostgreSQL, n8n, OpenAI, Claude, LangChain, LangGraph, MCP, Pinecone, Whisper, ElevenLabs. I'm bilingual, Arabic and English. I handle the full system: auth, billing, infra, all of it. Not just the AI parts. If you want a working system instead of a research notebook, send me what you're trying to build.

  • Python
  • Machine Learning
  • Artificial Intelligence
  • Neural Network
  • Deep Learning
  • AI Chatbot
  • Generative AI
  • AI Agent Development
  • AI Model Integration
Syed Muhammad Jarrar U.

Lahore, Pakistan

$35/hr
5.0
4 jobs

๐—™๐—ฟ๐—ฒ๐—ฒ ๐—”๐—œ ๐—ฆ๐—ผ๐—น๐˜‚๐˜๐—ถ๐—ผ๐—ป ๐—”๐—ฟ๐—ฐ๐—ต๐—ถ๐˜๐—ฒ๐—ฐ๐˜๐˜‚๐—ฟ๐—ฒ ๐—ฅ๐—ฒ๐˜ƒ๐—ถ๐—ฒ๐˜„ ๐—ฎ๐—ป๐—ฑ ๐—ข๐—ฝ๐˜๐—ถ๐—บ๐—ถ๐˜‡๐—ฎ๐˜๐—ถ๐—ผ๐—ป ๐—ฅ๐—ฒ๐—ฐ๐—ผ๐—บ๐—บ๐—ฒ๐—ป๐—ฑ๐—ฎ๐˜๐—ถ๐—ผ๐—ป๐˜€ ๐—•๐—ฒ๐—ณ๐—ผ๐—ฟ๐—ฒ ๐—ฃ๐—ฟ๐—ผ๐—ท๐—ฒ๐—ฐ๐˜ ๐—ž๐—ถ๐—ฐ๐—ธ๐—ผ๐—ณ๐—ณ. ๐—›๐—ถ, ๐— ๐˜† ๐—ป๐—ฎ๐—บ๐—ฒ ๐—ถ๐˜€ ๐—๐—ฎ๐—ฟ๐—ฟ๐—ฎ๐—ฟ. ๐—œ'๐˜ƒ๐—ฒ ๐—ฎ ๐— ๐—ฎ๐˜€๐˜๐—ฒ๐—ฟ'๐˜€ ๐—ฑ๐—ฒ๐—ด๐—ฟ๐—ฒ๐—ฒ ๐—ถ๐—ป ๐—–๐—ผ๐—บ๐—ฝ๐˜‚๐˜๐—ฒ๐—ฟ ๐—ฆ๐—ฐ๐—ถ๐—ฒ๐—ป๐—ฐ๐—ฒ ๐—ณ๐—ฟ๐—ผ๐—บ ๐—š๐—ฒ๐—ผ๐—ฟ๐—ด๐—ถ๐—ฎ ๐—ง๐—ฒ๐—ฐ๐—ต (๐˜๐—ผ๐—ฝ ๐Ÿฑ% ๐—ถ๐—ป ๐—จ๐—ฆ ๐—ถ๐—ป ๐—–๐—ฆ). ๐—œ ๐—ฎ๐—น๐˜€๐—ผ ๐—ต๐—ฎ๐˜ƒ๐—ฒ ๐Ÿณ+ ๐˜†๐—ฒ๐—ฎ๐—ฟ๐˜€ ๐—ผ๐—ณ ๐—ฒ๐˜…๐—ฝ๐—ฒ๐—ฟ๐—ถ๐—ฒ๐—ป๐—ฐ๐—ฒ ๐—ฝ๐—ฟ๐—ผ๐˜ƒ๐—ถ๐—ฑ๐—ถ๐—ป๐—ด ๐—”๐—œ ๐˜€๐—ผ๐—น๐˜‚๐˜๐—ถ๐—ผ๐—ป๐˜€ ๐˜๐—ผ ๐—™๐—ผ๐—ฟ๐˜๐˜‚๐—ป๐—ฒ ๐Ÿญ๐Ÿฌ๐Ÿฌ ๐—ฐ๐—น๐—ถ๐—ฒ๐—ป๐˜๐˜€ ๐—น๐—ถ๐—ธ๐—ฒ ๐—”๐—ง&๐—ง ๐—ฎ๐—ป๐—ฑ ๐—ฉ๐—ฒ๐—ฟ๐—ถ๐˜‡๐—ผ๐—ป. ๐—”๐—ฑ๐—ฑ๐—ถ๐˜๐—ถ๐—ผ๐—ป๐—ฎ๐—น๐—น๐˜†, ๐—œ ๐—ฟ๐˜‚๐—ป ๐—บ๐˜† ๐—ผ๐˜„๐—ป ๐—”๐—œ ๐—ฐ๐—ผ๐—ป๐˜€๐˜‚๐—น๐˜๐—ฎ๐—ป๐—ฐ๐˜† ๐—ต๐—ฎ๐˜ƒ๐—ถ๐—ป๐—ด ๐˜€๐—ฒ๐—ฟ๐˜ƒ๐—ฒ๐—ฑ ๐Ÿฏ๐Ÿฑ+ ๐—•๐Ÿฎ๐—• ๐—ฐ๐—น๐—ถ๐—ฒ๐—ป๐˜๐˜€. Are repetitive workflows, inefficient operations, slow customer support, poor lead qualification, disconnected systems, or manual business processes limiting your growth? I help businesses design, develop, and deploy production-ready AI solutions that automate operations, improve customer experiences, reduce costs, and increase team productivity. My focus is not on building demos or experimental prototypes. I build scalable AI systems that solve real business problems and deliver measurable outcomes. With extensive experience in AI Agent Development, Generative AI, Voice AI, RAG Pipelines, Workflow Automation, and Full-Stack AI Applications, I help startups, agencies, and enterprises transform their operations using modern AI technologies. ๐—ช๐—›๐—ฌ ๐—–๐—Ÿ๐—œ๐—˜๐—ก๐—ง๐—ฆ ๐—ช๐—ข๐—ฅ๐—ž ๐—ช๐—œ๐—ง๐—› ๐— ๐—˜ โžœ Production-ready AI systems designed for real-world business use โžœ AI agents that automate repetitive tasks and workflows โžœ Custom chatbots trained on your business knowledge โžœ Voice AI assistants for sales, support, and appointment booking โžœ RAG systems that retrieve accurate information from documents โžœ End-to-end development from architecture to deployment ๐—ฆ๐—˜๐—ฅ๐—ฉ๐—œ๐—–๐—˜๐—ฆ ๐—œ ๐—ฃ๐—ฅ๐—ข๐—ฉ๐—œ๐——๐—˜ โžœ AI Agent Development โžœ Multi-Agent Systems โžœ LangGraph Development โžœ LangChain Development โžœ AI Workflow Automation โžœ Generative AI Solutions โžœ OpenAI Integration โžœ Claude AI Integration โžœ Gemini AI Integration โžœ Llama & Open Source LLM Solutions โžœ Retrieval-Augmented Generation (RAG) โžœ Document Intelligence Systems โžœ Knowledge Base Chatbots โžœ Customer Support AI Agents โžœ AI Sales Agents โžœ AI Lead Generation Systems โžœ AI Research Assistants โžœ AI Content Automation โžœ Voice AI Development โžœ AI Receptionist Solutions โžœ Appointment Booking Agents โžœ Twilio Voice Solutions โžœ VAPI Development โžœ Retell AI Development โžœ WhatsApp Automation โžœ CRM Automation โžœ GoHighLevel Automation โžœ n8n Automation โžœ Make Automation โžœ Zapier Automation โžœ API Integration โžœ Full-Stack AI Application Development ๐—”๐—œ ๐—ง๐—˜๐—–๐—›๐—ก๐—ข๐—Ÿ๐—ข๐—š๐—œ๐—˜๐—ฆ โžœ OpenAI GPT-4o โžœ Claude โžœ Gemini โžœ Llama โžœ Mistral โžœ LangGraph โžœ LangChain โžœ LangSmith โžœ LlamaIndex โžœ Model Context Protocol (MCP) โžœ CrewAI โžœ AutoGen โžœ Hugging Face โžœ Prompt Engineering โžœ Fine-Tuning โžœ AI Evaluation Frameworks ๐—ฅ๐—”๐—š & ๐—ฉ๐—˜๐—–๐—ง๐—ข๐—ฅ ๐——๐—”๐—ง๐—”๐—•๐—”๐—ฆ๐—˜๐—ฆ โžœ Pinecone โžœ Qdrant โžœ ChromaDB โžœ FAISS โžœ Weaviate โžœ Hybrid Search โžœ Semantic Search โžœ Embeddings โžœ Document Processing โžœ Metadata Filtering ๐—ฉ๐—ข๐—œ๐—–๐—˜ ๐—”๐—œ ๐—ฆ๐—ง๐—”๐—–๐—ž โžœ Retell AI โžœ LiveKit โžœ Pipecat โžœ Twilio โžœ Deepgram โžœ Whisper โžœ AssemblyAI โžœ ElevenLabs โžœ PlayHT โžœ Azure Speech ๐—”๐—จ๐—ง๐—ข๐— ๐—”๐—ง๐—œ๐—ข๐—ก ๐—ฆ๐—ง๐—”๐—–๐—ž โžœ n8n โžœ Make โžœ Zapier โžœ GoHighLevel โžœ CRM Integrations โžœ Email Automation โžœ SMS Automation โžœ WhatsApp Automation โžœ Lead Management Automation ๐—™๐—จ๐—Ÿ๐—Ÿ-๐—ฆ๐—ง๐—”๐—–๐—ž ๐——๐—˜๐—ฉ๐—˜๐—Ÿ๐—ข๐—ฃ๐— ๐—˜๐—ก๐—ง โžœ Python โžœ FastAPI โžœ Django โžœ Flask โžœ Node.js, Express.js, NestJS โžœ React โžœ Next.js โžœ TypeScript โžœ Flutter โžœ PostgreSQL โžœ MongoDB โžœ Firebase โžœ REST APIs โžœ GraphQL APIs โžœ WebSockets โžœ Docker โžœ AWS โžœ Google Cloud โžœ Microsoft Azure ๐—ฃ๐—ฅ๐—ข๐—๐—˜๐—–๐—ง๐—ฆ ๐—œ ๐—–๐—”๐—ก ๐—›๐—˜๐—Ÿ๐—ฃ โžœ AI Customer Support Systems โžœ AI Appointment Booking Platforms โžœ AI Call Center Solutions โžœ AI SDR Agents โžœ Lead Qualification Systems โžœ Legal Document AI โžœ Medical Document AI โžœ Financial Research AI โžœ Compliance Automation โžœ Contract Analysis Systems โžœ Enterprise AI Platforms โžœ Multi-Tenant SaaS Applications โžœ Internal Company Assistants โžœ AI Workflow Automation Platforms ๐—œ๐—ก๐——๐—จ๐—ฆ๐—ง๐—ฅ๐—œ๐—˜๐—ฆ โžœ Healthcare โžœ Financial Services โžœ Legal โžœ Insurance โžœ Real Estate โžœ SaaS โžœ E-Commerce โžœ Logistics โžœ Staffing โžœ Telecommunications โžœ Education โžœ Professional Services ๐—ช๐—›๐—ฌ ๐—–๐—›๐—ข๐—ข๐—ฆ๐—˜ ๐— ๐—˜ โžœ Business-first approach focused on measurable ROI โžœ Strong software engineering and AI architecture expertise โžœ Clear communication and transparent project management โžœ Scalable and maintainable solutions โžœ Secure and enterprise-ready development practices โžœ Reliable post-launch support and optimization AI Agent Development, AI Agent Developer, LangGraph, LangChain, RAG, Retrieval Augmented Generation, Voice AI, AI Chatbot, OpenAI, GPT-4o, Claude, Gemini, Llama, Generative AI, AI Automation, n8n, Make, Zapier, GoHighLevel, FastAPI, Python, Next.js, React, Twilio, VAPI, Retell AI, Pinecone, Qdrant, ChromaDB, FAISS, LlamaIndex, MCP, Multi Agent Systems

  • Artificial Intelligence
  • AI Agent Development
  • AI Development
  • Machine Learning
  • Multimodal Large Language Model
  • AI Image Generator
  • Chatbot Development
  • LangChain
  • Retrieval Augmented Generation
  • AI Model Training
  • Large Language Model
  • Natural Language Processing
  • LLM Prompt
  • OpenAI API
  • Claude
  • Automation
  • API Integration
  • n8n
  • Twilio
  • AI Video Generator
Rajesh K.

Bangalore, India

$75/hr
5.0
67 jobs

๐Ÿ’ฌ โ€œRajesh consistently moved swiftly from ideation to a working product, accelerating timelines and delivering great results.โ€ โ€” Rotem Alaluf, CEO, Wand.ai ๐Ÿ’ฌ โ€œThroughout my career, Iโ€™ve worked with many developers, engineers, and CTOs, but Rajesh stands out.โ€ โ€” Khaled Azar, Serial Founder & M&A Advisor โšก 15 years building software | Nearly 10,000 Upwork hours | 50+ five-star projects | Production AI systems used by tens of thousands I build ambitious AI products โ€” especially multi-agent systems, GraphRAG, AI automation, and voice AI. Bring me in when the problem is technically difficult, the path from idea to production isnโ€™t obvious, and you need someone who can own the problem rather than just implement a specification. ๐Ÿš€ SOME OF THE SYSTEMS Iโ€™VE BUILT ๐Ÿข WAND.AI โ€” MULTI-AGENT AI PLATFORM AT SCALE Built on Wandโ€™s core AI platform: agents that execute code, work with email and calendars, search files, use tools, and maintain long-term memory. A production system used by tens of thousands of people, running on GCP with event-driven architecture, Kubernetes, and CI/CD. ๐Ÿ“ˆ COINQUANT โ€” MULTI-AGENT AI TRADING PLATFORM Built multi-agent architecture that turns trading strategies described in plain English into structured, validated, backtestable strategies. Manager agents orchestrate specialized Strategy and Domain agents working across 30โ€“40 custom tools, with LangSmith observability across the graph. Used by tens of thousands of users. ๐Ÿ”— GRAPHRAG โ€” GLOBAL COMMERCIAL-VEHICLE MANUFACTURER Built a hybrid knowledge-graph + vector-retrieval pipeline to automate complex event-to-component mapping over unstructured technical data โ€” work previously performed manually by domain experts. ๐Ÿ’ป MULTI-AGENT AI CODING SYSTEM Built a software-development system where specialized agents collaborate across complex coding tasks, each with its own responsibilities, context, tools, and execution capabilities. ๐Ÿงช MULTI-AGENT EVALUATION SYSTEM Built evaluation and regression infrastructure for agentic systems: datasets, automated evaluations, execution tracing, observability, and regression testing to catch behavioral changes as models, prompts, tools, and architectures evolve. ๐Ÿค MULTI-TENANT AI SUPPORT Built multi-agent support systems spanning different organizations, knowledge bases, tools, and workflows โ€” including orchestration, tenant isolation, retrieval, tool execution, and escalation. ๐ŸŽ™๏ธ REAL-TIME VOICE AI Built real-time multi-agent voice systems, including an AI interviewer designed to operate at roughly a tenth of the usual cost, with voice-activity detection, interruption handling, noise cancellation, and low-latency agent orchestration. ๐Ÿง  WHAT I CAN BUILD FOR YOU โš™๏ธ Multi-agent architecture & orchestration ๐Ÿงช Evaluation, observability & regression testing ๐Ÿ”— GraphRAG & knowledge graphs ๐Ÿ’ป AI coding & automation systems ๐Ÿ› ๏ธ Tool-using agents & MCP integrations ๐Ÿง  Memory & complex agent state ๐ŸŽ™๏ธ Real-time voice AI ๐Ÿš€ Open-source models & vLLM โ˜๏ธ GCP, Kubernetes, serverless & CI/CD I work across the full system. Commercial APIs when theyโ€™re the right fit. Open-source models when they make technical or economic sense. Kubernetes when the product needs it; a clean Ubuntu deployment when it doesnโ€™t. The technology serves the product โ€” not the other way around. ๐ŸŽฏ If youโ€™re building an ambitious AI product and need someone who can understand the problem, figure out the architecture, and move from idea to a working production system, letโ€™s talk.

  • Python
  • AI Agent Development
  • AI Bot
  • AI Chatbot
  • LangChain
  • Neo4j
  • Vector Embedding
  • Vector Database
  • React
  • Next.js
  • AI Code Generator
  • Google Cloud Platform
  • Amazon Web Services
Mohammed A.

Muscat, Oman

$50/hr
4.9
152 jobs

Iโ€™m Mohammed โ€” an AI Systems Architect, Software Engineer, Certified Requirements Engineer, and senior WordPress/WooCommerce expert with 16+ years of experience building business-critical digital platforms. Today, I help businesses design and build practical AI systems: AI agents, RAG assistants, automation workflows, LLM-powered apps, internal tools, and AI features connected to real business processes. My advantage is simple: I combine deep software engineering experience with modern AI engineering, so the result is not just a chatbot demo โ€” it is a usable, maintainable, and business-focused system. ๐Ÿ’กWhat I build: โœ… AI agents that reason, use tools, automate tasks, and connect to business systems โœ… RAG assistants that answer from documents, PDFs, websites, knowledge bases, or internal data โœ… LangGraph, CrewAI, AutoGen, and OpenAI Agents SDK workflows โœ… n8n automation connected to Gmail, Google Sheets, Google Drive, CRMs, APIs, Stripe, Telegram, and business tools โœ… AI-powered chatbots for support, education, sales, HR, operations, and e-commerce โœ… Python, FastAPI, Streamlit, Gradio, and API-based AI applications โœ… AI features inside WordPress, WooCommerce, LMS platforms, SaaS products, and existing web systems Whether you need an AI assistant trained on your company data, an automation workflow that saves hours every week, or a production-ready AI-powered web application, I can help plan it, build it, test it, and improve it. ๐Ÿ’กCore AI & Automation Expertise: โ€ข AI agents and multi-agent systems โ€ข Retrieval-Augmented Generation (RAG) โ€ข Vector databases and semantic search โ€ข LangChain and LangGraph โ€ข OpenAI API, Anthropic/Claude, and open-source LLMs โ€ข n8n AI automation workflows โ€ข Prompt engineering and structured outputs โ€ข Tool calling and function calling โ€ข AI-as-a-judge evaluation workflows โ€ข LLM/RAG evaluation and quality improvement โ€ข Fine-tuning concepts, QLoRA, Hugging Face, and model benchmarking โ€ข Speech recognition, transcription, and audio intelligence โ€ข Responsible AI, privacy guardrails, and risk-aware AI implementation I think about AI systems from both sides: the technical architecture and the business outcome. That means I care about reliability, cost, latency, UX, maintainability, data privacy, and measurable value. ๐Ÿ’กRelevant AI Systems I've Built (My portfolio includes): โ€ข Evaluated RAG knowledge workers for business Q&A โ€ข LangGraph support agents with persistent memory โ€ข n8n automation agents for accounting, SEO, legal operations, and real estate workflows โ€ข Multi-agent deep research systems with planning, web search, reports, and email delivery โ€ข AI privacy guardrails for safer ChatGPT use in business teams โ€ข AI meeting and call intelligence tools using speech recognition โ€ข AI interview coaches, course tutors, and knowledge-base chatbots โ€ข AI agents using CrewAI, AutoGen, OpenAI Agents SDK, LangGraph, and MCP-style tool integrations ๐Ÿ’กWordPress, WooCommerce & Web Engineering Background: Before focusing deeply on AI engineering, I spent 16+ years building and improving WordPress, WooCommerce, and custom web platforms. I have hands-on experience with custom plugins, themes, WooCommerce workflows, LMS platforms, booking systems, multivendor stores, memberships, LearnDash, H5P, GamiPress, ACF, Gravity Forms, Elementor, Divi, Gutenberg, CRM integrations, payment gateways, APIs, performance optimization, database debugging, custom PHP, JavaScript, React, and Vue.js. This background matters because many businesses do not need AI in isolation. They need AI integrated into their website, store, CRM, internal tools, support process, learning platform, or existing software stack. ๐Ÿ’กWhy Work With Me: When you work with me, you are not just hiring someone to write prompts or connect APIs. You are working with someone who can understand requirements, translate business goals into technical architecture, choose the right AI approach, build clean systems, connect AI with real tools and databases, and think about reliability, safety, scalability, and long-term improvement. I can help with idea validation, architecture planning, MVP development, workflow automation, AI feature integration, debugging, optimization, and scaling. ๐Ÿ’กLet's Build: If you are looking to: โœ… Build an AI agent or RAG assistant โœ… Automate business workflows with AI and n8n โœ… Add AI features to your website, SaaS, WooCommerce store, or internal platform โœ… Turn documents, calls, emails, spreadsheets, or business data into intelligent workflows โœ… Design a practical AI system that is actually useful for your team or customers Send me a message and letโ€™s discuss the best way to turn your idea into a working, high-impact solution.

  • AI Agent Development
  • Generative AI
  • Artificial Intelligence
  • OpenAI API
  • Business Process Automation
  • Retrieval Augmented Generation
  • Computer Vision
  • Chatbot Development
  • Machine Learning
  • API Integration
  • SaaS Development
  • Automation
  • Solution Architecture
  • AI Mobile App Development
  • AI Consulting
  • AI Security
  • AI Governance
  • AI Development
  • AI App Development
  • AI Product Management
Tahir H.

Lahore, Pakistan

$35/hr
4.8
185 jobs

Most developers will build exactly what you spec. The problem is that what gets specced is rarely what actually solves the business problem. The gap between those two things is where AI projects fail, and closing that gap before writing any code is how I work. I have been building production AI systems and full-stack platforms for several years. Not prototypes. Systems that handle real users, real data and real consequences when something breaks. TaxForce is a 37-agent system running inside a real CPA firm covering document intake, risk scoring, audit defense, deadline tracking and client communication. The Facebook Self-Healing Ads platform is a closed-loop AI system that monitors, diagnoses and fixes campaign performance without human intervention. PAM AI handles thousands of concurrent dealership calls across 8 plus CRM integrations. Dentva is a HIPAA-compliant SaaS handling patient scheduling in production daily. These are not templates strung together, they are properly engineered systems with error handling, logging and recovery paths built in from the start. Before this I spent a year and a half at Turing doing RLHF and model evaluation on the OpenAI and Claude model families. That experience shapes how I evaluate AI output and design systems that behave reliably rather than impressively in demos. On the full-stack side I was CTO on RIZZ, a React Native dating app that grew past 100K users. I have worked on Junia AI, Slides and TopSocialAI across multi-tenant architecture, real-time systems and mobile at scale. These are confirmed production experience not claimed skills. The stack I work in daily is Next.js, React, TypeScript, Python FastAPI, Node.js, Supabase, PostgreSQL, LangChain, LangGraph, OpenAI, Anthropic API, Retell AI, Vapi, Twilio, ElevenLabs, Deepgram, n8n, Make and AWS. If you are building something in agentic systems, AI automation, full-stack SaaS or voice AI and you want someone who will tell you honestly what the right approach is before agreeing to build it, that is the conversation I am interested in having.

  • Artificial Intelligence
  • Machine Learning
  • Python
  • Natural Language Processing
  • Computer Vision
  • Deep Learning
  • Data Science
  • TensorFlow
  • Automation
  • Large Language Model
  • Generative AI
  • LangChain
  • AI Agent Development
  • AI Model Development
  • n8n
  • Make.com
  • OpenAI API
  • ChatGPT
  • API Integration
  • Next.js
Daniel E.

Eeklo, Belgium

$50/hr
4.8
6 jobs

Most AI systems die between the demo and production. I build the ones that survive โ€” and everything I claim is public. โœ” agentic-rag-mcp (open source): a multi-agent RAG server over MCP where every answer cites its exact source chunk or the agent refuses. The eval suite โ€” groundedness, citations, refusal correctness โ€” runs in CI, so a regression fails the build. โœ” mcp-vitals (open source): a CLI that grades any MCP server Aโ€“F for reliability and agent-usability. I graded the official reference servers โ€” two got an A, one got an F. Live report published. โœ” groundcheck (open source): a 1.5B groundedness-judge I fine-tuned (QLoRA) that agreed with a frontier judge 100% of the time at $0 per call โ€” shipped only because its own evals beat the baseline. โœ” drumvia (live in production): a SaaS marketplace built solo end to end โ€” auth, Stripe payments, KYC, real-time bidding, row-level security. Next.js, React 19, Supabase. WHAT I DELIVER โ€ข MCP servers โ€” your API exposed to Claude/ChatGPT/agents: strict schemas, auth, remote deployment, observability, evals. Fixed scope. โ€ข RAG systems with real citations โ€” hybrid retrieval (pgvector) + reranking; grounded answers, measured quality. โ€ข AI agents & automation โ€” LangGraph pipelines, tool-calling, deterministic gates, human-in-the-loop; n8n + Claude workflows. โ€ข AI reliability & evals โ€” golden datasets, LLM-as-judge, eval harnesses wired into your CI. HOW I WORK Evaluation-first. I fix problems at the right layer โ€” tool, gate, or prompt โ€” then lock each fix with a regression test. Clear milestones, funded escrow, async updates. The boring reliability stuff โ€” retries, idempotency, graceful failure โ€” is what actually keeps a system alive. Tell me what your AI is supposed to do, and I'll tell you how to prove it does it.

  • AI Image Generator
  • AI Video Generation
  • Node.js
  • API Integration
  • ChatGPT API Integration
  • Claude
  • Supabase
  • AI Agent Development
  • REST API
  • LangChain
  • n8n
  • PostgreSQL
  • Automated Workflow
  • Python
  • Web Scraping
  • Prompt Engineering
  • Data Analytics
  • FFmpeg
  • Automation
  • Generative AI

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LangGraph specialist hiring guide

LangGraph specialists build sophisticated agentic AI systems that go beyond simple chatbots, impacting workflows from customer service orchestration to automated research systems. These professionals design multiagent workflows where AI assistants collaborate, make decisions, and adapt based on complex state management and control flow. 

What does a LangGraph specialist do?

A LangGraph specialist designs, builds, and deploys agentic AI workflows using the LangGraph framework for orchestrating complex language model applications. Unlike traditional developers who work with simple prompt chains, these specialists create AI systems that can reason through multiple steps, maintain state across interactions, and coordinate between multiple autonomous agents. LangGraph specialists bring technical depth in Python, LangChain integration, and production-ready AI deployment.

Core responsibilities for LangGraph specialists include:

  • Building multiagent systems. Different AI agents collaborate on complex tasks, each with specialized roles and capabilities.

  • Implementing state management. AI applications remember context across conversations and handle interruptions gracefully using LangGraph's built-in state persistence.

  • Designing control flow. They build graphs where agents can loop back, branch based on conditions, and adapt their approach dynamically.

  • Integrating tools and APIs. AI agents take actions beyond text generation by querying databases, calling external services, and interfacing with business logic.

  • Adding human-in-the-loop workflows. AI agents pause for human approval and escalate complex decisions to human oversight.

How to hire a LangGraph specialist on Upwork

Finding the right LangGraph specialist starts with clearly defining your agentic AI requirements and evaluating candidates based on technical depth, portfolio quality, and communication skills.

Step 1: Craft a targeted job post

A well-crafted job post helps attract LangGraph specialists with direct experience in the specific agentic AI patterns your project demands.

  • Describe your project clearly, including specific deliverables like a multiagent customer service system or workflow automation with human oversight.

  • Specify required technical skills such as Python, LangChain, state management, and familiarity with LLM APIs.

  • Outline your current tech stack, integration requirements, and expected timeline.

For a faster starting point, try the Job Post Generator, powered by Umaโ„ข, Upwork's Mindful AI. Describe your needs in a few sentences and Uma will draft a LangGraph job post for your review and customization.

Step 2: Evaluate candidates

Focus on evidence of real-world implementations that demonstrate mastery of LangGraph's graph-based architecture and state persistence capabilities.

  • Review candidate profiles to verify practical experience with complex agent systems.

  • Look for multiagent system examples with documented workflows and clear state management.

  • Check for production deployments that include error handling and monitoring via LangSmith.

  • Leverage Best Match insights, powered by Uma, to identify top proposals.

Step 3: Interview your top choices

Live conversations reveal how candidates think through complex agentic AI challenges and communicate technical concepts.

  • Conduct interviews to assess their technical problem-solving approach.

  • Ask candidates to walk through a multiagent system they've built and explain their state management approach.

  • Inquire about human-in-the-loop workflows and when they would choose LangGraph over simple LangChain.

  • Schedule interviews within Upwork Messages, utilizing the recording feature for transcripts and summaries.

Step 4: Agree on scope and begin work

Defining explicit deliverables and payment structures in a contract up front prevents scope creep throughout the development life cycle.

  • Establish clear contract terms and project milestones before development begins.

  • Choose between fixed-price contracts for defined deliverables or hourly contracts for ongoing optimization.

  • Set clear milestones for larger projects such as architecture design, core implementation, tool integration, and deployment.

  • Rely on Upwork's Hourly Payment Protection and project funds features for security.

Upwork is not affiliated with and does not sponsor or endorse any of the tools or services discussed in this article. These tools and services are provided only as potential options, and each reader and company should take the time needed to adequately analyze and determine the tools or services that would best fit their specific needs and situation.

The rates and information provided in this article are based on current data and industry sources available at the time of publication. Freelance rates can vary depending on factors such as experience, location, project scope, and market conditions. Readers are encouraged to conduct their own research to confirm current rates and trends, as this information may change over time.

How much does hiring a LangGraph specialist cost?

Hiring a LangGraph specialist typically ranges from $35 to $60 per hour, similar to other AI engineers. For pricing information on related specialties, see Upwork's rate guide for in-demand skills

Below are typical cost ranges for LangGraph projects commonly found on Upwork.

Single-agent workflow implementation

$500-$1,500/project

Entry-level to mid-level
  • One agentic workflow with basic state management
  • Single LangChain tool integration
  • Local deployment with documentation

Multiagent orchestration system

$2,000-$5,000/project

Mid-level to senior-level
  • Coordinated multiagent pipeline with tool integration
  • Human-in-the-loop approval workflows
  • LangSmith monitoring setup

Enterprise agentic AI application

$5,000-$15,000/project

Senior-level to expert
  • Production-grade agent system with advanced state persistence
  • Custom node types and security implementation
  • Full deployment and integration testing

Ongoing optimization and support

$1,500-$4,000/month

Mid-level to senior-level
  • Performance monitoring and agent refinement
  • Workflow updates and LangSmith analytics
  • Monthly reporting and improvements

AI architecture strategy and training

$10,000-$25,000/project

Expert or consultant-level
  • Agentic AI roadmap and framework evaluation
  • Multiteam training sessions
  • Governance planning and scalable infrastructure design

FAQs about LangGraph specialists

Frequently asked questions

Is hiring a LangGraph specialist worth it?

Yes, hiring a LangGraph specialist is worth it when your AI application needs are beyond simple chatbots or linear prompt chains. If you're building systems requiring multiple AI agents working together, complex decision-making with loops and branches, or stateful workflows, a specialist helps save significant time and avoid costly mistakes.

The learning curve for LangGraph is steep, requiring understanding of graph-based architectures and state management patterns. A specialist brings this expertise up front, providing ROI through faster time to market and scalable AI systems.

What should I look for in a LangGraph specialist's portfolio?

When reviewing a LangGraph specialistโ€™s portfolio, look for practical experience with complex agent systems, state management implementations, and tool integrations. Strong portfolios demonstrate multiagent examples showing coordination between specialized agents.

Additionally, look for production deployments with error handling, LangSmith monitoring, and scalability considerations. Clear documentation explaining architectural decisions and workflow diagrams indicates a qualified specialist.

Do I need a LangGraph specialist or can I use LangChain alone?

You can use LangChain alone for simpler applications with linear workflows, but you need a LangGraph specialist for cyclical workflows where agents loop back and refine their reasoning.

Consider LangGraph when you need complex state management, multiagent coordination, or human-in-the-loop workflows. A LangGraph specialist understands both frameworks and can recommend the right fit.

Whatโ€™s the difference between LangGraph and other agent frameworks?

LangGraph differentiates itself through explicit graph-based control flow and deep integration with the LangChain ecosystem. Unlike CrewAI or AutoGen which focus on autonomous multiagent collaboration, LangGraph gives developers precise control over workflow structure, state management, and native human oversight through pause points.