LangGraph Agent Engineer Needed

@ZohaibRoy

⭐⭐⭐⭐⭐ Build and Optimize Your LangGraph Agent Platform with Expertise ❇️ Hi My Friend, I hope you are doing well. I just reviewed your project details and see you are looking for an Agent Engineer. You don't need to look any further; Zohaib is here to help you! My team has successfully completed 50+ similar projects related to agent platforms. I will create and optimize the agent framework, ensuring it meets your requirements while providing fast and accurate language-model pipelines. ➡️ Why Me? I can easily handle your agent platform project as I have 5 years of experience in system design and development, focusing on Python, NLP, and LangGraph. My expertise includes building frameworks, optimizing performance, and delivering working code efficiently. I also have a strong grip on clean architectural patterns, which will benefit your project. ➡️ Let's have a quick chat to discuss your project in detail, and I can show you samples of my previous work! I'm looking forward to discussing this with you. ➡️ Skills & Experience: ✅ Python Programming ✅ LangGraph SDK ✅ System Design ✅ Language Modeling ✅ NLP Optimization ✅ Architecture Diagrams ✅ Test Suite Creation ✅ Docker Deployment ✅ Code Reviews ✅ Agile Methodologies ✅ Performance Profiling ✅ Collaboration on GitHub Waiting for your response! Best Regards, Zohaib

@OutsourceMan

⭐⭐⭐⭐⭐ Having CnELIndia take on your LangGraph Agent Engineer project means you are entrusting the task to a seasoned team with over 18 years of industry experience. Our expertise in Python guarantees the efficient creation, optimization, and maintenance of your language-modeling components. We have built systems using various libraries and frameworks similar to LangGraph which equips us with a deep understanding of SDK internals. Moreover, our extensive experience in delivering web and app development projects makes us code-review experts who can provide valuable suggestions to improve the system's design and performance. We dedicate ourselves to providing clean architectural solutions and our proficiency in Docker ensures smooth deployments. Collaboration is key, and we ensure effective daily communication through Slack and meticulous code reviews via GitHub. Our delivery model aligns perfectly with your sprint requirements and our monthly payout system will provide you a sense of security throughout the project. Choose CnELIndia for this project and rest assured about receiving a first working agent MVP plus test suite with reproducible benchmarks, an architecture diagram with a decision log, deployment scripts and more!

@divumanocha

With over a decade's worth of experience, my team and I are the ideal choice for your LangGraph Agent Engineer project. Not only do we have exquisite proficiency in Python, Django and Natural Language Processing (NLP), we also boast a comprehensive understanding of modern language modeling tools, which makes us the perfect fit to design, develop and optimize your agent framework from scratch. Our competency doesn't end there. Having worked extensively with Docker, we can provide you with precise and efficient deployment scripts for foolproof execution of your project. Further ensuring quality deliverables, we are well-versed in various collaboration tools such as Slack and GitHub, utilizing them thoroughly to ensure smooth workflow and consistent communication with you. At the end of the day, it is not just our skill set in Python or our proficiency in building innovative NLP functionalities that sets us apart; it's our dedicated approach towards your project that guarantees a significant stride forward. Thanks...

@Rekhathakur

As a highly skilled Engineer, I have a deep understanding of the linguistic complexities that come with language modeling and processing components like LangGraph. My core skills in Natural Language Processing, extensive experience in working with modern LLM frameworks and Python, as well as my knowledge of clean architectural patterns will ensure I can meet your project requirements with utmost accuracy and efficiency. Additionally, my background in Software Architecture will be valuable in designing and building the agent framework from scratch, optimizing language-model pipelines and delivering clean code every sprint. Moreover, I have consistently displayed excellence in collaborating effectively, ensuring a smooth communication loop with daily check-ins on Slack and code reviews on GitHub. My understanding of the importance of quick iterations based on feedback perfectly aligns with your project's approach. Thanks....

@Herculesz

Hi The main technical challenge in this project is building a LangGraph agent platform that stays modular and fast while keeping the core language-processing pipeline accurate, testable, and easy to evolve across rapid sprint cycles. I can take ownership of the system design and implementation using Python and LangGraph, with a strong focus on graph orchestration, agent state flow, prompt/tool routing, memory design, and robust execution patterns. My approach would be to design the framework from the core outward, defining clear node responsibilities, state schemas, retry/error handling, and evaluation checkpoints so the agent remains reliable as complexity grows. I also focus on profiling bottlenecks in LLM pipelines, reducing latency, improving determinism where needed, and structuring the codebase so experiments do not turn into technical debt. I can deliver a working MVP quickly with a CLI or lightweight web UI, reproducible benchmarks, Dockerized setup, and a clean runbook for the team. GitHub-based reviews, sprint demos, and fast iteration fit well with how I usually work on agent systems. My background in Python, LLM workflows, agent architecture, and maintainable system design makes me a strong fit for this role. Thanks, Hercules

@nikhilgarg96

Hi, This is a perfect match for my expertise in building LLM-powered agent systems and scalable AI architectures. I can immediately take ownership of designing and developing your LangGraph-based agent platform with a strong focus on performance, modularity, and rapid iteration. I have solid experience working with Python, LLM pipelines, RAG systems, and workflow orchestration, and I’m comfortable going deep into LangGraph internals to optimize accuracy, latency, and reliability. I follow clean architectural patterns and can deliver a working MVP quickly, along with benchmarks, test coverage, and Docker-based deployment. I’m also aligned with your sprint cadence (fortnightly sprints, daily Slack updates, GitHub reviews) and can commit full-time to maintain consistent delivery. A few quick questions: Which LLM providers are you currently using (OpenAI, open-source, hybrid)? Any preference for memory/state management approach within LangGraph? Should the initial MVP prioritize CLI or lightweight web interface? Ready to start immediately. With Regards!

@Ekarthaan

Hi Ven K., This is quite similar to a project I delivered last week, so I can jump straight into execution. Ready to start immediately. Which base models/backends are in scope (OpenAI/Azure, Anthropic, or local via vLLM), and should tools be invoked via native function-calling or explicit tool nodes with schema-validated IO? Should the agent graph be a mostly static DAG with conditional edges, or support runtime subgraph planning/replanning, and what memory model do you prefer (sliding window + episodic notes vs long‑term vector/DB-backed)? Suggestion 1: Implement a provider-agnostic ModelRouter with latency/cost-aware routing and optional vLLM for batchable steps; add a Redis-backed LLM cache to de-dup prompt+context responses and cut p95 latency/cost. Suggestion 2: Use LangGraph Checkpointer on Postgres for durable state and replay/time-travel, paired with golden-trace evaluations and OpenTelemetry logs to prevent drift and catch regressions each sprint. Action Plan: - Phase 1: Requirements + design; confirm tools/memory/QoS; deliver architecture diagram + stack log. - Phase 2: MVP: typed State (pydantic), core nodes, control flow, checkpointer; CLI demo. - Phase 3: Benchmarks: datasets, accuracy/latency/cost metrics; profiling; prompt/model/routing tuning. - Phase 4: Hardening: retries/backoff/timeouts/guards; test suite + reproducible evals. - Phase 5: Deploy: Docker, CI (GitHub Actions), env/config, runbook. Best Regards, Sid

@hireageek

Hi there, I understand that you're looking for a dedicated Agent Engineer to take charge of the design and development of your LangGraph-powered agent platform. With my extensive background in software development, machine learning, and deep knowledge of modern language models, I'm confident in my ability to optimize your language-model pipelines for speed and accuracy. Having successfully completed similar projects, I thoroughly understand the importance of delivering working code promptly, ensuring seamless iterations based on feedback. I’m based in California and have been recognized as a top freelancer on this platform, earning five-star reviews for my commitment and results. I'm ready to jump in immediately and collaborate closely through daily check-ins and fortnightly sprints. Let's discuss how we can align our goals and kick off the first sprint at your earliest convenience. What specific challenges do you anticipate with the language-model pipelines that I should be aware of? Best regards,

@corpmember29

HELLO, WITH STRONG EXPERIENCE IN LANGUAGES MODELS, PYTHON, AND SYSTEM DESIGN, I CAN TAKE FULL OWNERSHIP OF DEVELOPING THE LANGGRAPH-POWERED AGENT PLATFORM. I WILL: Design & Build: Develop the agent framework from the ground up, ensuring it's optimized for both accuracy and speed. Optimize Pipelines: Work on optimizing the language-model pipelines within LangGraph to meet performance requirements. Iterative Development: Ship working code each sprint, demo progress, and incorporate feedback rapidly. Deliverables: Provide architecture diagrams, tech stack decisions, an MVP (CLI or lightweight web UI), a test suite with reproducible benchmarks, and a deployment script. I have a solid grasp of modern LLMs and am well-versed in Python and LangGraph SDK internals. I’m ready to start immediately and commit to a full-time monthly retainer with daily check-ins and code reviews. LOOKING FORWARD TO DISCUSSING THE FIRST SPRINT. THANKS!

@Feriver

Hello, I can take full ownership of designing and developing your LangGraph-powered agent platform, focusing exclusively on language-modeling and processing pipelines. I will deliver a robust architecture that optimizes LLM workflows for accuracy, speed, and scalability, while maintaining clean, maintainable code. The first sprint will produce a working agent MVP (CLI or lightweight web UI), accompanied by architecture diagrams, tech stack decisions, a test suite with reproducible benchmarks, and deployment scripts with a concise runbook. I follow iterative sprints with rapid feedback incorporation, ensuring tangible progress each cycle. I have strong expertise in Python, NLP, LLM optimization, and clean software architecture patterns, with experience profiling and tuning language-model pipelines for production workloads. Full-time commitment and sprint cadence are feasible immediately. Thanks, Asif

@dvcontact

Hello Sir, Would you be interested in a demo showcasing how our LangGraph-powered agent platform can exceed your expectations, even before we commence our partnership? With my expertise in Python, LLMs, and the LangGraph SDK, I am poised to take full ownership of the system design and development, optimizing language-model pipelines for both accuracy and speed. I invite you to discuss this further and explore a detailed plan for the project, along with the demo that will showcase the potential impact of our collaboration. Regards, Smith

@devendrathakur12

Hello, Can we discuss about your LangGraph agent platform project cause I have built LLM pipelines with structured workflows and performance tuning for fast iterations. I can design the core agent system, optimize pipelines, and deliver MVP with Docker using Python and LangGraph. How will you measure agent accuracy across tasks? Do you need memory persistence or stateless flows first? What latency target should each step meet? Small thing: poor prompt/state design slows systems more than model choice. Best regards, Devendra S.

@jinufeb14

As one of the top-ranked freelancers on the platform, I am uniquely positioned to fulfill your needs for an Agent Engineer. My ML expertise, mastery of Python, and deep understanding of software architecture make me an ideal candidate to design, build, and optimize language-modeling pipelines within LangGraph for the best accuracy and speed possible. My career has seen me creating innovative solutions using cutting-edge technologies, and as such I have a holistic understanding of how different components fit together. I can assure you a customized solution that will perfectly align with your project's needs while consistently shipping working code every sprint. I also bring to the table my skills in clean architectural patterns as well as optimizing and profiling NLP workloads, which are direct value-adds for your project. I believe effective communication and regular feedback loops are crucial in ensuring steady progress and delivery - something I will actively maintain with you through daily check-ins on Slack and code reviews on GitHub. Let us lock in the first sprint together to kick start this ambitious project!

@abhisaini0188

Hello, With over 8 years of experience in software development, I believe I would be the perfect fit for your LangGraph Agent Engineer role. My work revolves around building intelligent systems with a strong focus on automation and machine learning integrations. This has sharpened my skills in working with languages models, such as LangGraph, optimizing language processing components, and utilizing Python proficiently to solve complex tasks. Having developed successful AI-powered web and mobile applications, I understand the significance of shipping working code every sprint and continuously refining it based on feedback. This aligned approach will not only ensure steady progress within fortnightly sprints but also ensure your core tech remains deepened without compromising any peripheral integrations handled by other teams. My expertise builds not just on working with LLMs, Python, and the LangGraph SDK internals but identifying clean architectural patterns to enhance system design. Moreover, my experience dealing with NLP workloads prove to be an added advantage for profiling and tuning NLP workloads you desire. With automated business processes through AI agents being another one of my strengths, I can assure you I will take full ownership of your project's design and development while delivering real business impact. Let's get started on your first sprint! With Regards! Abhi

@johnallenvillan1

Hello, your need for someone to take full ownership of the LangGraph agent platform stood out, especially your emphasis on deep work in the language‑modeling layer while other teams handle integrations. I’ve built similar LLM‑centric agent systems, including a LangGraph workflow where I delivered a full pipeline redesign that cut inference latency by 32% and added structured benchmarking for iterative tuning. I see the real challenge here being the architectural discipline needed to keep the graph logic clean while supporting rapid iteration. Poor separation between state transitions, tool calls, and model steps can cause hard‑to‑debug drift over sprints, something I’ve solved before by enforcing deterministic graph nodes and reproducible evaluation harnesses. I’ll map the architecture, implement the agent backbone in Python with LangGraph SDK, add a minimal CLI/UI wrapper, and create a benchmark suite with profiling hooks. I’ll also containerize the system with a reproducible deployment script and keep all decisions logged for clarity. Before we lock in the first sprint, I’d like to confirm expectations around full‑time availability and your preferred benchmarking metrics. Thanks, John allen.

@juanjosec63

Hi, As a individual developer and I can jump into on your suitable time. I can help in your project (most important in this project libraries, modules, and relative issue during this project fix, improve, development) With my expertise in full-stack development and experience working with modern technologies like Python, LangGraph, LLM pipelines, NLP optimization, FastAPI, Docker, and scalable system architecture, i can design and build your agent platform from scratch with efficient language-model workflows, reproducible benchmarks, and clean deployment-ready structure. You can expect clear communication, fast turnaround, and a high-quality result that fits seamlessly into your existing workflow. Best regards, Juan

@ivaylo8

Hello, I’m Ivaylo, and I’m excited to partner with you to build a LangGraph-powered agent platform in India, taking full ownership of design and core NLP engineering. You’re looking for a focused, high-velocity result, a robust agent framework, optimized LLM pipelines, and repeatable, sprint-driven progress. I will design an end-to-end architecture, establish a clean tech stack and decision log, and ship a first MVP (CLI or lightweight UI) with a solid test suite and reproducible benchmarks. Expect architecture diagrams, performance-tuned components, and deterministic demos every sprint, with Dockerized deployment and a concise runbook for operations. I’ll collaborate in fortnightly sprints with daily Slack check-ins and GitHub reviews, ensuring quality while adapting quickly to feedback. I’m ready for immediate start, full-time monthly engagement, and I’ll maintain momentum to keep milestones on track. Best regards, Ivaylo

@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

@juanestebana17

Hi, With extensive experience in NLP, Python, and LLMs, I am ready to take full ownership of your LangGraph-powered agent platform from design through deployment, ensuring rapid iterations and high-quality outputs. What specific challenges have you encountered with your current system that you want addressed in this project? Thanks, Juan Aponte