Senior LangGraph & LangChain Specialist (Agentic AI) – Hourly Contract

@MashoodurRehman1

As a Senior AI Specialist with strong expertise in LangGraph and LangChain, I have developed complex agentic systems in production environments. My hands-on experience with these technologies, particularly in designing and optimizing workflows and logic, makes me well-suited for this role. I possess solid Python skills and have successfully collaborated within existing codebases to improve agent behavior and system reliability. I have extensive experience refining agent workflows and fixing inconsistencies in agent systems. By utilizing LangGraph for effective workflow design and LangChain for advanced logic management, I ensure efficient agent operations. My past work includes addressing performance and cost efficiency issues and enhancing multi-step decision-based agents, which aligns closely with your project needs. I am keen to discuss how I can contribute to scaling and optimizing your AI agents. Could you share more about specific challenges you're facing? I can provide code samples and more insights upon request. Looking forward to exploring how I can support your project's success.

@AwaisChaudhry

Hello, I’m Muhammad Awais, a LangGraph and LangChain expert with hands-on production experience. You need someone to design, fix, and scale agent workflows in an existing setup, not a demo. My approach is to start with a quick audit of current flows, state handling, and tool routing, then implement robust LangGraph orchestration and LangChain logic (chains, tools, memory, routing). I’ll improve reliability, performance, and cost by refactoring flaky paths, hardening state management, and adding observability, tests, and safe deployment practices within your codebase and CI/CD. In a real production project, I redesigned multi-step agents with LangGraph, slashed latency, reduced errors, and tightened memory usage while keeping business logic intact. I can share GitHub links or code samples if available. I’ll work with your existing codebase and governance while delivering measurable improvements. What is your current LangGraph version and LangChain setup, and what is the size of the production agent fleet? What are the top pain points (latency, reliability, cost) you want to address first? How many concurrent agents do you expect, and what are the throughput/SLAs? Are there any data privacy or compliance constraints I must align with? What is your preferred approach to testing and rollout (staged deployments, feature flags, canary)? Best regards,

@ZohaibRoy

⭐⭐⭐⭐⭐ Expert in LangGraph and LangChain for AI Agent Development ❇️ Hi My Friend, I hope you're doing well. I've reviewed your project requirements and see you are looking for a specialist in LangGraph and LangChain. You have no need to look any further; Zohaib is here to help you! My team has successfully completed 50+ similar projects for AI agent development. I will design and refine workflows, fix existing issues, and enhance the performance of your agents within your budget. ➡️ Why Me? I have 5 years of experience in building and improving AI agents using LangGraph and LangChain. My skills include designing workflows, fixing agent flows, and optimizing performance. I also have a strong grip on Python and problem-solving, ensuring I can address any challenges effectively. ➡️ Let's have a quick chat to discuss your project in detail and let me show you samples of my previous work. I look forward to discussing this with you in our chat. ➡️ Skills & Experience: ✅ LangGraph ✅ LangChain ✅ Python Programming ✅ Workflow Design ✅ Agent Development ✅ Performance Optimization ✅ State Management ✅ Problem Solving ✅ Multi-Agent Systems ✅ Debugging ✅ Code Collaboration ✅ Cost Efficiency Waiting for your response! Best Regards, Zohaib

@Herculesz

Hi I can help you refine, repair, and scale your existing LangGraph + LangChain agents with a production-first mindset, not a demo-oriented one. The core challenge in systems like yours is inconsistent state transitions and poorly defined edges between nodes, and I solve this by restructuring the graph, tightening state management, enforcing deterministic routing, and optimizing tool boundaries for cost and reliability. I’ve used LangGraph in real deployments where agents handled multi-step decision flows, external API calls, and conditional branching under strict SLAs. I also improve LangChain pipelines by reducing unnecessary LLM calls, adding retries/backoff, and consolidating memory/state so agents behave predictably. My Python experience is strong, and I work directly inside existing codebases without rewriting architecture unless necessary. I can begin by diagnosing your current graphs and stabilizing the most brittle state paths first. Thanks, Hercules

@hireageek

Hi there, I’m excited about the opportunity to contribute to your LangGraph and LangChain projects. With a proven track record as a top California freelancer and extensive experience in building and refining agent workflows, I understand the nuances of designing efficient systems in production. In a previous role, I successfully used LangGraph to enhance an AI agent's performance, focusing on multi-step decision-making processes that align with real business logic. When addressing inconsistencies in agent systems, my first approach is to analyze the agent's state handling and workflow design, ensuring that all components function cohesively. I'm adept at improving system reliability, performance, and cost efficiency. I’m ready to dive deep into your existing codebase and begin optimizing agent flows immediately. Could you provide more details about the specific challenges you're facing with the current agent workflows? Best regards,

@denisSolution

Hello client, I'm Denis Redzepovic, an experienced developer with expertise in Python, AI Development, LangChain, AI Agents, AI Chatbot Development, Chatbot and AI Consulting. I have worked extensively on diverse Python projects, ranging from backend development and automation to data processing and API integrations. My deep understanding of Python’s libraries and frameworks allows me to build efficient, scalable, and maintainable solutions. I pay close attention to code quality and performance to ensure your project runs flawlessly. With my solid experience, I’m confident I can deliver results that exceed your expectations. I focus on writing clean, maintainable, and scalable code because I know the difference between 99% and 100%. If you hire me, I’ll do my best until you’re completely satisfied with the result. Let’s discuss your project details so I can tailor the perfect Python solution for you. Thanks, Denis

@juanjosec63

Hello, I’m excited about the opportunity to work on your existing production agents and help stabilize, scale, and refine LangGraph-based workflows. I’ve used LangGraph in real systems to model stateful, multi-step agent flows where reliability mattered more than novelty, and most of my work has involved fixing inconsistent state transitions, broken routing, and hidden coupling between tools, memory, and prompts rather than building demos. When agents behave unpredictably, I usually start by auditing state definitions, entry/exit conditions, and tool side effects, then tighten graph boundaries and reduce unnecessary LLM calls to improve determinism, latency, and cost. I’m comfortable working inside established Python codebases, reasoning about business logic, and improving agent architectures incrementally without disrupting production, and I can share relevant code samples if needed. Best regards, Juan

@sasaprogramer21

I work hands on with LangGraph and LangChain in real production agent systems, not demo chatbots. I have built multi step decision workflows where state, tool routing, retries, and cost control matter as much as the model output. One LangGraph project I delivered was an operations agent that orchestrates ticket triage, knowledge retrieval, action tooling, and escalation using explicit graph state, guarded transitions, and human in the loop nodes. LangGraph was used to enforce deterministic flow, prevent looping, and make failures observable and recoverable. When an agent behaves inconsistently, I fix these first: State contract and mutation points: ensure the graph state is minimal, typed, and not leaking context Tool reliability: timeouts, idempotency, and structured tool outputs to avoid prompt drift Routing logic: explicit decision nodes instead of implicit LLM wandering Memory and retrieval: verify grounding, chunking, and citations so agents stop hallucinating Cost and latency: reduce unnecessary calls, add caching, batch where possible, and tighten prompts I write clean Python, add trace level observability, and stabilize workflows before adding new complexity. I can share code samples or private repos depending on your NDA needs.

@vasudharao9

Hi, I am a Computer Science graduate from UC Berkeley with a specialization in Artificial Intelligence. I have more than 10 years of experience in the AI and ML industry. I have experience training and finetuning AI models. I can help you with this project. Message me to discuss this further. Thanks

@shanec35

Hello, I have carefully analyzed your requirements and recently completed a production LangGraph-based multi-step agent system for a SaaS platform, where I redesigned faulty state handling, improved graph routing logic, and stabilized long-running workflows using LangChain tools, memory, and custom decision nodes. Your project needs strong LangGraph workflow design, deep LangChain logic, reliable state management, and performance optimization, and I will address this by auditing existing graphs, refactoring broken transitions, improving memory and tool orchestration, optimizing token usage, and implementing clear control-flow for multi-step business decisions. I am available to begin work immediately and am committed to delivering the highest quality improvements within the shortest possible timeframe. Best regards, Elenilson

@mykhaylob4

✋ Hi there. I can step into an existing LangGraph and LangChain codebase and fix, refine, and scale agent workflows that are already running in production. ✔️ I have deep hands-on experience with LangGraph state graphs, node routing, conditional edges, and shared state handling, combined with advanced LangChain usage beyond basic chains. In a recent production project, I worked on decision-based agents where I fixed unstable state transitions, tool call loops, memory leaks, and incorrect routing that caused inconsistent outputs and high token cost. ✔️ For your setup, I will first inspect graph structure, state design, memory scope, and tool execution flow to find where logic breaks under real load. I will refactor agent steps, clean up routing rules, improve error handling, and tune prompt and tool usage to reduce latency and cost while keeping behavior predictable. ✔️ I will work directly inside your existing Python codebase, make focused changes, and explain what was fixed and why. I am comfortable collaborating on non-greenfield systems and improving agents without breaking live workflows. Let’s chat to review your current agent issues and priorities. Best regards, Mykhaylo

@JijoThomas2020

Hi, I’m a senior ML engineer with hands-on production experience using LangGraph and advanced LangChain, focused on fixing and scaling real agent systems (not demos). I’ve used LangGraph to refactor unstable agent workflows into explicit, deterministic graphs with clear state handling, routing, and recovery paths. These were live systems with inconsistent behavior, and my work focused on making them predictable, debuggable, and cost-efficient. What I fix first when agents misbehave: - Broken or implicit state management - LLM-driven control flow instead of graph-driven logic - Overloaded agents that should be tools or sub-graphs - Prompt logic leaking business rules - Missing observability and retry paths I’m comfortable working inside an existing codebase, improving reliability, latency, and cost without rewriting everything. Hourly, remote, flexible, and outcome-driven. Happy to share GitHub/code samples or jump straight into a concrete issue. Best, Jijo

@webmasters486

Hi there, I’ve carefully reviewed the requirements for your GenAI project and I’m confident that my expertise in building NLP pipelines using Hugging Face and LangChain can meet your expectations. My experience includes working with large language models (LLMs) for Retrieval-Augmented Generation (RAG), as well as fine-tuning models with custom datasets to enhance text generation. I’ve successfully completed similar projects where I applied these techniques in Python to build robust, client-specific solutions. I would love the opportunity to discuss how I can leverage my skills to develop a tailored solution for your project. Feel free to take a look at my portfolio to get a sense of the work I’ve done: Portfolio: https://www.freelancer.com/u/webmasters486 Looking forward to hearing from you! Best regards, Muhammad Adil

@xuezhe315

Hello, With a wealth of experience particularly in AI Agents and Python, I am a natural fit for your project. I have an intimate and extensive understanding of the LangGraph and LangChain tools, which goes far beyond basic chains, meaning I can jump into your project at a deep level, swiftly identifying solutions to challenges and improving workflows with precision. Throughout my career, I've built intricate software systems for numerous clients that have proven successful in real-world applications. For instance, I used LangGraph to design a complex agentic system that significantly improved supply chain management for one of my past clients, reducing costs by 15% within three months. When it comes to troubleshooting inconsistent agent behaviors, my approach is systematic and efficient. I typically begin by scrutinizing the state handling across the agent flows – it's essential to ensure they are designed and maintained correctly for optimal functionality. My strategy centers around steady reliability, superior performance, and cost efficiency – all traits that align closely with your project’s goals. To provide you with a concrete demonstration of my skills and work approach, I'd be glad to share specific projects on my GitHub page where I've leveraged LangGraph and other relevant technologies like Python to create practical solutions. Let's turn your ideas into realities together! Best Wishes,

@KarthikTechCon

Hi, I’m Karthik, a Python/AI engineer with 10+ years of experience and strong hands-on work in LangChain and LangGraph for production agent systems. I work on real agent workflows—not demos—focusing on reliability, state control, and cost-aware scaling. I’ve built and debugged multi-step agents with tools, memory, and routing logic, and I’m comfortable joining existing codebases to fix what’s already live. Relevant experience ✔ Designed LangGraph flows for multi-step decision agents (tool use + conditional routing + persistent state) ✔ Built LangChain systems with custom tools, retrievers, memory, and guardrails ✔ Improved latency/cost via prompt optimization, caching, and smarter model routing ✔ Strong Python, async patterns, and structured debugging When agents behave inconsistently, I first: Inspect state transitions & memory usage Validate tool I/O contracts and retries Check prompt/chain determinism and fallback logic Add tracing + observability to isolate failure points I’m comfortable with agent orchestration concepts and outcome-driven work. Happy to share code samples/GitHub in chat. Available hourly, remote, and for long-term collaboration if there’s a good fit. If you need someone practical who can stabilize and scale agents, I’m ready to jump in.

@Azursol

Dear Juan Carlos L., I am a Python developer specializing in Chatbot and AI Consulting with a strong background in LangChain and AI development. Your project requiring a Senior LangGraph & LangChain Specialist aligns perfectly with my expertise. I have successfully designed and implemented advanced logic using LangChain, ensuring reliable agent workflows and enhancing performance. My hands-on experience in LangGraph and deep understanding of agentic systems make me well-equipped to address the challenges your project presents. I am committed to clear communication, reliable delivery, and problem-solving to meet your project goals effectively. I am eager to discuss how we can collaborate to achieve success. Best regards,

@hassansuhail

Hello, I’ve reviewed your job and can help refine, fix, and scale your existing LangGraph and LangChain agents to improve reliability, performance, and cost efficiency. I focus on diagnosing workflow inconsistencies, optimizing chain/tool usage, and ensuring multi-step, decision-based agents run predictably in production. I’ve used LangGraph in a production AI assistant project where I mapped agent workflows, implemented memory handling, and optimized routing across multiple tools to handle dynamic user intents. When an agent behaves inconsistently, I first check state propagation, memory sync, and tool invocation order to identify where the logic fails. Happy to review your workflows and advise on next steps. Cheers, Hassan Suhail

@ayesha0124

Hi there, I understand you're looking for a true specialist in LangGraph and LangChain to enhance your existing AI agents. With extensive hands-on experience in these technologies, I've successfully designed and refined workflows that prioritize reliability and efficiency. In my previous role, I worked on a project where I integrated LangGraph to streamline agent interactions, which significantly reduced processing time and enhanced decision-making capabilities. When facing inconsistent behaviors in agent systems, I typically start by diagnosing the state management and workflow integrity to pinpoint bottlenecks. My strong Python skills and structured problem-solving approach have consistently driven positive outcomes. I look forward to discussing how I can contribute to your team's success. I can provide GitHub links and code samples upon request.

@ravd82

As a versatile professional well-versed in a multitude of technologies, I bring to the table a unique blend of skills and experience that makes me a strong fit for your project. While my expertise spans across Front End, Back End development and Mobile App development, I have substantial hands-on experience in Python which directly aligns with your project requirements. When it comes to LangGraph and LangChain, you need someone who doesn't just possess awareness but has the technical know-how to design, scale, fix and improve existing AI agents running in production - exactly what I bring. I've previously worked on multiple projects involving LangGraph where I had to solve complex problems with clear thinking and structured problem-solving approach - attributes crucial for designing and refining agent workflows. Moreover, I understand that building agentic systems demands more than creating simple chains - it's about using them effectively to build reliable, performant and cost-efficient models. My prior experience also includes building such systems in production that would aptly serve your real-business logic needs. Beyond just completing assigned tasks, I believe in long-term collaborations where my performance speaks volumes. Excited by the scope of this project and eager to showcase my expertise, I hope you will consider employing me to continue elevating your agents to the next level.