Agentic AI Specialist Needed

@corpmember29

PRODUCTION-GRADE AGENTIC AI SYSTEMS REQUIRE MORE THAN PROMPTS — THEY NEED RELIABLE ORCHESTRATION, TOOL CONTROL, AND REAL-WORLD ERROR HANDLING. With 12+ years of experience in AI systems, SaaS automation, backend engineering, and scalable cloud architectures, we have hands-on expertise building multi-agent AI workflows for real production environments including automation pipelines, AI assistants, scheduling systems, CRM integrations, and intelligent business operations. Our experience includes: • Multi-agent orchestration using LangGraph, CrewAI, AutoGen & custom agent loops • Claude/OpenAI/Gemini integrations • MCP server integrations & live context handling • AI voice workflows & scheduling agents • Email automation & lead qualification systems • CRM, POS, calendar & third-party API integrations • Retry logic, fallback systems & hallucination control • Async Python architecture & scalable API services • Debugging agent loops and tool-execution failures in production Preferred Stack: Python, FastAPI, LangGraph, CrewAI, Claude APIs, Redis, PostgreSQL, Docker, async workflows, and cloud deployment infrastructure. If you share your current agent architecture or workflow examples, I can immediately suggest optimization opportunities and the most reliable implementation approach for scaling your AI systems.

@InterconnectBPO

Hi, We can design and build production-grade agentic AI systems for your small business clients, focusing on reliable automation across voice ordering, email workflows, scheduling, and estimate generation tools. Our team has hands-on experience building multi-agent systems using Python with frameworks like LangGraph, CrewAI, and AutoGen, with strong emphasis on clean async architecture, API integrations, and maintainable code structure. We integrate agents with CRMs, POS systems, calendars, and email platforms while ensuring stable tool execution, retry logic, fallback handling, and production debugging for issues like hallucinations, loop failures, and tool-use errors. We also configure MCP servers to connect agents with live data sources and manage context efficiently for reliable outputs. We are comfortable working within your $3–$8/hr range on a flexible contract or retainer basis. Regards Interconnect Team

@faizanmaqbool695

I am already working on these projects i can give send you Demo as well I have carefully reviewed your project requirements and I am confident that I can deliver exactly what you are looking for with high quality and efficiency. I bring practical experience, attention to detail, and a strong commitment to meeting deadlines. My goal is always to provide work that not only meets but exceeds client expectations.

@jinufeb14

As a seasoned AI specialist, I have the technical prowess and hands-on experience to deliver successful agentic AI systems for your small business clients. My expertise with technologies like Claude Code, LangGraph, AutoGen, or CrewAI is well-documented on my GitHub. Additionally, my proficient Python skills – covering everything from async coding to clean repo structure – will ensure that your multi-agent systems are efficient and properly integrated with external APIs. One area where my expertise strongly aligns with your project needs is understanding and working with LLM APIs such as Anthropic Claude. I have spent a considerable amount of time building AI pipelines with such APIs, making me fully equipped to seamlessly manage data transactions between your multi-agent system and various platforms like CRMs, POS systems, calendars, and email platforms. Moreover, my experience with orchestration frameworks (like LangChain, LangGraph, CrewAI) and MCP servers for connecting agents to live data strengthens my ability to debug complex issues—be it agent loops or hallucination concerns--even in high-pressure production environments. So, if you're seeking a diligent and capable professional who truly understands the demands of real production builds (and not just demos), let's discuss how we can optimize your agentic AI system for success together!

@toriquldev123

Hello There! I’m an experienced full-stack developer specializing in Agentic AI systems, Python automation, and multi-agent orchestration, with over 10 years of experience building production-grade AI workflows and API-driven platforms. I understand you need an AI specialist to build and maintain multi-agent systems for real business use cases like voice bots, scheduling agents, email automation, and estimate generators using frameworks like LangGraph, CrewAI, and Claude-based workflows. I’ve worked on similar agent pipelines involving API integrations, tool orchestration, MCP connections, and production debugging. My skills in Python, LangGraph, Claude API, async systems, MCP servers, and AI workflow automation ensure scalable and reliable delivery. Feel free to share more details. I’m ready to start immediately and discuss project scope and long-term collaboration. Looking forward to hearing from you. Best regards, Md Toriqul Islam

@muteebu007

Experienced Agentic AI developer specializing in building real-world multi-agent systems for voice bots, scheduling agents, email automation, and operational workflows for small businesses. Skilled with Claude Code, LangGraph, CrewAI, AutoGen, and custom Python agent architectures with strong async design, clean repo structure, and production-grade reliability. I can integrate agents with CRMs, POS systems, calendars, email platforms, and MCP servers to create live, context-aware automation pipelines. Strong focus on debugging hallucinations, tool failures, loop control, retry logic, and fallback behavior to ensure stable deployment beyond prototype stage. I build scalable AI systems designed for efficiency, automation, and measurable ROI rather than simple demos. Available for contract or retainer work and ready to provide relevant project examples/GitHub demonstrating production agent builds.

@Srashtasoft

Hi there, I have read your project requirement. You need an Agentic AI Specialist to build and maintain multi-agent AI systems for real-world production use cases such as voice ordering bots, scheduling agents, email automation pipelines, and estimate generators. We have experience working with Python, AI orchestration frameworks, API integrations, and scalable backend architectures. Our team can help design reliable multi-agent workflows, integrate with third-party systems like CRMs and calendars, configure MCP servers, and optimise production stability with proper retry logic, fallback handling, and debugging. A few questions: ============= Which orchestration framework are you currently using or planning to use — LangGraph, CrewAI, AutoGen, or custom architecture? Are the MCP servers already configured, or should we handle setup as well? Which CRM/POS/email platforms need to be integrated initially? Do you already have existing agent workflows/codebases or are we building from scratch? We are comfortable working in fast-moving production environments and maintaining clean, scalable repository structures. Best Regards, Srashtasoft Team

@billybryan98

Hello there, I hope you are doing well. I’m an individual AI developer with hands-on experience designing and deploying multi-agent AI pipelines, specializing in voice ordering bots, scheduling agents, and automation workflows. I’ve built production-grade agent systems using Claude Code, LangGraph, AutoGen, and CrewAI, with robust Python services, async processing, and clean repo structures. In past projects, I connected agents to CRMs, calendars, POS, and email platforms via resilient API integrations, implemented MCP server wiring for live data, and added strong error handling, retry logic, and fallback strategies to keep agents reliable. I’ve tackled hallucinations and tool-use failures in production, improving stability with monitoring and guardrails. I can handle this work end-to-end, drawing on my experience to deliver scalable, maintainable agent networks that meet small business needs. I can start quickly and propose a phased plan with milestones. Best regards, Billy Bryan

@enocki8

Hi, Your project stands out because it focuses on real production-grade agentic systems rather than simple demo automations. The combination of multi-agent orchestration, MCP integration, tool reliability, and production debugging is exactly where structured AI engineering becomes important. My experience includes working with: * Python-based AI workflows * API integrations and automation pipelines * Prompt engineering and agent behavior optimization * AI-assisted backend systems * Structured orchestration workflows and tool-use logic * Claude-based development environments and AI workflow systems I’m comfortable building and maintaining: * Scheduling and workflow agents * Email automation systems * CRM-integrated AI pipelines * Multi-step tool execution logic * Fallback and retry handling for unstable agent flows * Context-aware agent interactions Technically, I’m comfortable with: * Async Python * REST APIs * MCP/tool integration concepts * LangGraph/CrewAI-style orchestration workflows * Repository organization and maintainable backend structure * Debugging hallucination loops and unreliable tool calls What I bring is strong analytical troubleshooting, clean implementation workflows, and the ability to work independently while keeping systems stable and maintainable as they scale. I’m available for ongoing remote collaboration and long-term production support. Enock

@juanpablomacf

Hi, I’m Juan Pablo — Agentic AI engineer with hands‑on experience building production multi‑agent systems using Claude Code, LangGraph, CrewAI, AutoGen and custom orchestration loops. I focus on reliability, tool‑use accuracy, and predictable behavior in real business workflows. What I bring to your team • Multi‑agent architectures with shared memory, tools and role‑based behaviors • Claude‑driven pipelines with structured outputs and deterministic tool‑use • API integrations (CRMs, POS, calendars, email, payments, internal systems) • MCP server configuration to connect agents with live data/services • Clean Python (async, retries, fallbacks, error boundaries) • Debugging of loops, hallucinations, tool failures and state drift • RAG, retrieval tools, and context‑window optimization • Git‑clean repo structure with modular agents and utilities Approach I design agents that behave consistently under load: clear roles, strict schemas, safe tool‑use, and guardrails to prevent runaway loops. I test edge cases, concurrency, and degraded‑network scenarios. My focus is production reliability, not demos. Experience I’ve built voice ordering bots, scheduling agents, email automation, estimate generators, and multi‑agent back‑office systems. Strong background in agent orchestration and Claude‑based tool pipelines. I can share GitHub examples, workflow demos, availability, and hourly rate. If helpful, I can also prepare a multi‑agent architecture outline before starting.

@AlexVydrin

Hi there — this is exactly the kind of agent work I like: real production systems where reliability matters more than flashy demos. I’m comfortable building multi-agent workflows in Python with frameworks like LangGraph, CrewAI, and custom orchestration loops, and I pay close attention to the parts that usually break in production: tool routing, retries, fallback behavior, loop control, and bad context management. I’ve worked on API-heavy automations where agents need to interact cleanly with CRMs, calendars, email systems, and external business tools, and I understand that MCP is useful precisely because it gives a cleaner way to connect models to live services without one-off glue everywhere. I’m also comfortable with Claude-centered builds, including handling context-window limits, tool-use failures, and escalation paths when the model should stop guessing and hand off instead. So if you need someone who can write clean async Python, debug agent failures in the real world, and help ship systems that small businesses can actually rely on, I’d be a strong fit. I can also share relevant code samples or repo structure from similar agent/API work as part of the application.

@SkillCrafts

Your project for building multi-agent AI systems for SMBs aligns perfectly with my recent work deploying autonomous workflows that reduce operational overhead. I recently architected a multi-agent system using LangGraph to coordinate specialized agents for automated lead qualification and CRM management, cutting manual processing time by nearly 60% for a mid-sized firm. I understand that for SMBs, the priority is creating a scalable, cost-efficient solution that integrates with existing tools like Slack or HubSpot to ensure immediate ROI and ease of adoption across the organization. My technical approach involves leveraging frameworks like CrewAI or LangGraph to build a modular "swarm" of agents, each assigned a granular role with specific tools and memory access. I prioritize a robust orchestration layer that handles state management and cyclical reasoning, ensuring agents can self-correct and verify outputs before final delivery. For SMB needs, I focus on integrating RAG (Retrieval-Augmented Generation) using Pinecone or Weaviate to provide agents with localized context, while optimizing token usage via smart model selection—balancing high-reasoning models like GPT-4o with faster, cost-effective alternatives. This ensures high performance without exceeding tight monthly operational budgets. To ensure the architecture fits your goals, are you prioritizing internal process automation like reporting, or are these agents intended for direct, client-facing interactions? Additionally, do you have a preferred tech stack for deployment, or would you like a recommendation on a serverless setup to minimize ongoing maintenance? I am available for a brief chat or a quick call today to discuss your vision in more detail and help you determine the most efficient roadmap for a production-ready prototype.

@kend27

Hi, I’m interested in helping you build production-ready agentic AI systems for small business clients. I have hands-on experience with Python-based AI automation, multi-agent workflows, API integrations, and LLM-powered pipelines for real business use cases, including email automation, scheduling logic, document processing, CRM-style workflows, and voice/assistant systems. I can design clean agent architectures using LangGraph, LangChain, CrewAI, AutoGen, or custom orchestration loops depending on the project requirements. I’m also comfortable integrating agents with external APIs, calendars, email platforms, databases, and business tools, while adding proper retry logic, error handling, fallback behavior, logging, and guardrails to reduce hallucinations and tool-use failures. My workflow is practical and delivery-focused: define the agent roles, connect the right tools and data sources, implement the Python backend, test edge cases, and make sure the system is reliable enough for production rather than just a demo. I also understand MCP concepts, context management, RAG-style retrieval, and how to debug agent loops when they fail. I’m available for remote freelance work and can support ongoing retainer-based projects. I’d be glad to share relevant project examples and start with a small task to prove fit.

@chiragardeshna

Hi there, Strong alignment with this project comes from experience delivering production-ready AI automation systems involving multi-agent workflows, API orchestration, real-time integrations, and scalable business process automation. Clear understanding of the requirement to build and maintain agentic AI pipelines for voice bots, scheduling systems, email automation, estimate generation, and live integrations with CRMs, calendars, POS systems, and external APIs. Hands-on expertise with Python, Claude APIs, LangGraph, CrewAI, LangChain, async workflows, MCP integrations, and AI orchestration frameworks ensures reliable automation behavior, clean architecture, and stable production deployment. Risk is minimized through structured debugging, fallback handling, retry logic, context management, and continuous monitoring of agent performance, tool execution, and workflow reliability. Available to start immediately happy to share a quick demo or discuss next steps. Recent work: https://www.freelancer.com/u/chiragardeshna Regards Chirag

@nicolasalexandro

I can help you design and deliver robust multi-agent AI systems tailored for SMEs, from initial concept through to deployment. I work specifically with agentic architectures where agents can coordinate, reason, and act autonomously around clear business goals. I’ve implemented multi-agent workflows for data enrichment, customer support, internal operations, and decision support, using frameworks like LangChain, OpenAI tools, and orchestration layers that integrate cleanly with existing SaaS stacks. My approach would be to clarify the business outcomes first, then define distinct agent roles, communication protocols, and guardrails, followed by an iterative build–test–refine cycle in a staging environment before production rollout. Quick question before I suggest an approach: Do you already have a preferred LLM stack or are you open to recommendations based on your existing infrastructure?

@rbtech1984

Hi There!!! ★★★★ ( Multi-agent AI systems with LangGraph, CrewAI, Claude APIs & production-ready automation workflows ) ★★★★ I carefully reviewed your project and understand you’re looking for an Agentic AI specialist to build real-world multi-agent systems for small business automation, including voice bots, scheduling agents, email workflows, and estimate generators. The focus on stable production deployments, MCP integration, and debugging agent behavior is exactly the kind of work I enjoy doing. ⚜ Multi-agent AI architecture ⚜ LangGraph / CrewAI development ⚜ Claude & LLM API integration ⚜ MCP server configuration ⚜ Python async & API workflows ⚜ Agent debugging & fallback logic ⚜ CRM, POS & calendar integrations I have hands-on experiance building AI automations and agent pipelines using Python, LangChain, CrewAI, and API-based orchestration systems. I focus on clean repo structure, reliable tool execution, retry handling, and reducing hallucination issues in production enviroments. I’m comfortable working with Anthropic APIs and integrating agents with live business systems. I’d love to discuss your current workflows and contribute to building scalable agentic systems that deliver real business value for your clients. Warm Regards, Farhin B.

@himanshus642

With my 5+ years as a seasoned Full Stack Developer, I have gained unparalleled expertise in various niches and developed solutions that prioritize scalability, security, and automation. I bring this extensive knowledge base to bear in helping small businesses build and optimize their workflow using your desired tech stack. Through successful engagements, I have built strong competencies in agentic AI, Python, API integration, Linux, and software architecture. Leveraging these skills, I have designed and implemented AI automation workflows for companies allowing them to experience seamless daily operations. By integrating AI (including Chatbots and RPA) into real workflows, I've managed to transform manual operations into highly automated ones. This has resulted in an exponential increase in productivity - a trait key to your project requirements as well. Choosing me would mean not only getting a reliable, highly skilled professional who is dedicated to the success of your project but also someone who is versatile enough to handle any challenges that may arise during execution. Together we will build impactful multi-agent AI systems ensuring quality codes with a keen eye for error handling and fallback behavior that guarantees smooth workflows every step of the way. My unique understanding of both technology and business goals means we can effectively maximize the capabilities of every tool and resource at our disposal.

@murtuza90

With thirteen years of technical refurbishments, I am confident that my skills fit the Agentic AI Specialist role you need filled. Throughout my career, I have excelled in constructing sophisticated applications, harnessing diverse Python frameworks like Anthropic Claude and LingGraph which squarely aligns with your requirement. My prior experience includes handling various systems like CRMs, POS networks, calendars, and email platforms - all critical components of the multi-agent AI ecosystem your organization focuses on. My proficiency in operating MCP servers efficiently intersects with your need to connect agents with live data and services. Additionally, my dedication to writing clean code with proper error handling, retry logic, and fallback behavior helps guarantee quality product delivery. Client satisfaction is at the core of my work ethic; I do not just deliver features but scalable, secure and future-ready systems built to drive ROI. My solid understanding of agentic AI technology and orchestration frameworks makes me more than just a software expert — it makes me a crucial asset needed to make the visions of your organization come to life. Feel free to reach out for further discussion so we can explore how best I can help augment your operations.

@umekayani01

Hey there, I can build stable multi agent workflows using Python with proper orchestration, API integrations, error handling, retries, and MCP style connections for CRMs, emails, calendars, and POS systems Logic: orchestrator agent breaks task → tool agent executes API calls → validator checks output → fallback handles failures → logs stored for reliability Focus is on real world stability, clean architecture, and avoiding agent loops or hallucinations in production Do you already have a preferred framework like Lang Graph or Crew AI or should I design a custom lightweight system Inbox me ASAP so we can start building production level agents Warm regards Umer Kayani