Senior AI Agentic Developer Needed

@sekai1116

I have extensive experience designing and deploying autonomous AI systems and agentic models in production. I’ve built multi-agent orchestrations where individual LLMs—specialized for tasks like reasoning, summarization, and API execution—collaborate through shared memory structures and vector stores. Using frameworks like LangChain, Semantic Kernel, and custom orchestration layers, I’ve created systems that break down complex user requests, assign specialized agents dynamically, and execute workflows with minimal human oversight. My work includes monitoring hallucination rates, optimizing context usage across agents, and benchmarking performance for mission-critical workloads deployed on cloud infrastructure with containerized pipelines and CI/CD automation. For your first milestone, I can deliver a proof-of-concept swarm capable of parsing a complex task, allocating subtasks to specialized agents, and consolidating outputs into an actionable plan. This POC will include evaluation metrics for robustness, correctness, and hallucination mitigation. I prioritize modular architecture so the system can scale to dozens of agents, integrate new LLMs or tools, and maintain reliability under production loads. My goal is to translate cutting-edge R&D into stable, scalable, and auditable agentic systems that meet real-world requirements.

@yuliussmayoru

Hello, Your focus on agentic architectures and swarm-based orchestration is exactly the space I’ve been working in recently. I design production-grade multi-agent systems where specialized LLMs collaborate through structured planning, shared memory, and tool execution. For your first milestone, I would architect the swarm around a planner–executor–evaluator pattern: • A Planner Agent that decomposes complex requests into task graphs • Specialized Worker Agents assigned dynamically based on capability • A shared vector memory layer (Qdrant/Weaviate/Pinecone) for context persistence • Tool execution layer for APIs, code, and external systems For orchestration I typically combine LangGraph or CrewAI with a lightweight custom coordination layer to support scalable agent routing, retry logic, and cost-aware model selection. Infrastructure would be containerized (Docker) and deployed via AWS/GCP with CI/CD, enabling reproducible benchmarking and rapid iteration. I also implement observability pipelines to track token usage, latency, and hallucination metrics across agents. My goal would be to deliver a robust PoC swarm that not only produces executable plans but also provides measurable reliability and evaluation metrics suitable for production scaling. If helpful, I can also share examples of autonomous agent pipelines and tool-calling reasoning systems I’ve built. Looking forward to discussing how we can bring this architecture into production.

@SkillCrafts

Your vision for a next-generation platform centered on agentic models aligns perfectly with my recent work developing high-scale autonomous systems and multi-agent architectures. I recently architected an enterprise-level environment where specialized agents for data synthesis, reasoning, and API execution were coordinated via a hierarchical supervisor model, resulting in a 40% improvement in task completion accuracy. I understand that moving from single autonomous agents to complex, multi-agent ecosystems requires a deep mastery of state management, tool-calling precision, and the ability to mitigate "hallucination loops" that often plague unsupervised workflows. To build a robust infrastructure for your platform, I will implement a state-driven framework like LangGraph or PydanticAI to manage complex cycles and persistent memory across long-running sessions. My approach focuses on modularity, where each agent is constrained by specific personas and toolsets, utilizing structured output schemas to ensure seamless inter-agent communication and data integrity. I will integrate a vector-based memory layer for contextual awareness and implement rigorous observability using LangSmith to trace reasoning paths and optimize token costs. By prioritizing asynchronous execution and fallback mechanisms, I ensure the platform remains resilient, high-performing, and capable of handling edge cases without system-wide stalls. Regarding the roadmap, do you plan to leverage a decentralized framework like AutoGen for emergent behavior, or do you prefer the deterministic control of directed graphs? I am also interested to know if your vision includes a "human-in-the-loop" interface for high-stakes decision nodes, as this impacts how we design the state persistence layer. Let’s connect to discuss your milestones—I am available for a chat or a call to align on the requirements and explore how my expertise in agentic development can accelerate your platform’s launch.

@Julian29

Hello, Senior AI Agentic Developer I have similar kind of expertise and work experience. I have 10+ years in AI systems, full-stack development, and LLM integration shine. I’ve built autonomous agent pipelines, reasoning chains, and vector-memory orchestration frameworks that handle real-world workflows reliably and scalably. Approach & Key Features -->> Architect modular agentic swarms with specialized LLMs that share memory via vector stores -->> Build planning & reasoning chains to decompose complex tasks into agent-specific actions -->> Integrate OpenAI, Anthropic, Llama 2/3 with LangChain, Semantic Kernel, or custom orchestration frameworks -->> Implement tool-calling, API pipelines, and memory management optimized for minimal hallucinations -->> Deploy containerized solutions to AWS/GCP/Azure with CI/CD and monitoring for production workloads -->> Provide evaluation metrics for robustness, performance, and hallucination tracking This approach ensures a scalable, production-grade agentic system capable of executing complex multi-agent workflows while remaining modular for future expansion or integration. Best regards, Julian

@juanjosec63

Hello, I’m excited about the opportunity to contribute to your project. With my expertise in agentic AI systems, LLM integrations, orchestration frameworks, and scalable cloud deployment, along with a strong focus on clean, scalable implementation, I can help design and implement autonomous agent architectures that coordinate multiple models, tools, and memory layers reliably. I’ll tailor the work to your exact requirements, building structured agent workflows, integrating leading LLMs with orchestration frameworks, optimizing context and vector memory pipelines, and delivering a proof-of-concept swarm capable of decomposing complex requests and coordinating specialized agents. You can expect clear communication, fast turnaround, and a high-quality result that fits seamlessly into your existing workflow. Best regards, Juan

@rbtech1984

Hello There!!! ★★★★ ( Senior AI Agentic Developer for Autonomous Systems ) ★★★★ I understand you are building a next-generation platform focused on agentic AI systems, including autonomous agents, swarms, and orchestration layers that coordinate multiple LLMs. The goal is turning R&D prototypes into scalable production-ready systems with strong reasoning and tool-calling capabilities. ⚜ Agentic AI architecture and autonomous workflow design ⚜ Multi-LLM orchestration using LangChain, CrewAI, Semantic Kernel ⚜ Tool-calling pipelines and external API integrations ⚜ Vector memory systems and context optimization ⚜ Cloud deployment with Docker, CI/CD pipelines ⚜ Performance benchmarking and hallucination monitoring ⚜ Scalable swarm-based agent coordination I have 9+ years experiance building advanced AI systems, automation platforms, and scalable backend architectures. Recently I’ve worked on LLM workflows, agent orchestration, and AI integrations for production apps. My approach would be designing modular agents, shared vector memory, and orchestration pipelines using Python, LangChain/CrewAI with OpenAI or Llama models deployed on AWS using containerized services. Would love to discuss the swarm PoC and your roadmap. Warm Regards, Farhin B.

@snbhanja

HI, I have worked on many agentic AI systesm including deep research agents, agent swarms etc using openai/anthropic claude models. The architecture includes vector DB and cache like redis for shared memory, memory compaction to save tokens, langgraph/agno/llamaindex/agentsdk etc based on usecase, minio/s3 for file storage, docker, docker compose, websockets/grpc based on usecase and CI/CD pipelines. Lets me know.

@Lazarone1

Hi, that’s great to hear! Your project closely aligns with one I recently completed. In that project, I built an agentic swarm architecture capable of orchestrating multiple specialised LLMs using OpenAI models, LangChain pipelines, and custom orchestration logic with containerised deployment, vector-store memory sharing, and automated evaluation metrics. Given your focus on production-ready autonomous agent swarms and scalable orchestration layers, I can help translate your R&D prototypes into robust systems that reason, plan, and act with minimal supervision. Your first milestone, building a proof-of-concept swarm that decomposes tasks, assigns specialised agents, persists shared memory, and produces a validated executable plan, fits directly within my past experience architecting multi-agent systems and tool-calling pipelines. I’d be glad to connect and share my experience in more detail over chat. Thank you. Best regards, Lazar

@ayesha86664

Hi there! Building production-ready agentic systems with multiple coordinated AI agents is complex, especially when reasoning, memory sharing, and orchestration must work reliably at scale. Turning research prototypes into stable systems requires strong architecture and careful experimentation. I have experience working with AI systems that integrate LLMs, agent frameworks, and cloud infrastructure. I’ve built AI workflows using OpenAI APIs, tool-calling pipelines, and automation systems that coordinate multiple tasks and services. My work also includes deploying scalable AI services with containerization and CI/CD on cloud platforms. My approach would focus on designing a modular agent architecture where specialised agents communicate through shared memory, vector storage, and orchestration layers. I’ll also implement evaluation metrics to monitor reasoning quality, stability, and hallucination rates while preparing the system for scalable deployment. Check our work https://www.freelancer.com/u/ayesha86664 Do you already have a preferred framework for the swarm orchestration such as LangChain or CrewAI? Let me know if you’re interested & we can discuss it. Best Regards Ayesha

@Hubready

Hello!, I am a US-based senior software engineer with extensive experience in AI development and automation. I carefully reviewed your project on building a next-generation platform centered on Agentic Models. I understand the importance of creating efficient and scalable AI solutions, and I believe my background aligns perfectly with your needs. With over 15 years in the field, I have successfully integrated AI-driven systems, focusing on text-to-speech, chatbots, and custom AI models. I’ve built AI-powered tools for various clients, ensuring their platforms not only function well but also deliver a strong ROI. Could you please clarify the following questions to help me better understand the project? 1. What specific functionalities are you envisioning for the Agentic Models? 2. Are there existing systems or APIs that the platform needs to integrate with? To ensure project success, I suggest we start with a thorough requirements analysis, followed by an agile development process. This way, we can iteratively refine the platform based on testing and feedback. I’m committed to delivering high-quality, maintainable solutions that drive your vision forward. I look forward to the opportunity to discuss this exciting project further! Best, James Zappi

@PrateekP3003

Hi There! I’ve gone through your project description for building production-ready Agentic Models and swarms orchestrating multiple specialized LLMs. I AM GLAD TO TELL YOU THAT I’ve already architected and shipped autonomous agent systems that coordinate multi-agent reasoning, memory sharing via vector stores, and tool/API orchestration pipelines. I am ready to help you turn your R&D prototypes into scalable, mission-critical Agentic Models with features like – Autonomous Agent Swarms: Task decomposition, specialized agent assignment, and execution plans with evaluation metrics for robustness and hallucination tracking. LLM Integration & Orchestration: OpenAI, Anthropic, Llama 2/3 integrated with LangChain, Semantic Kernel, or custom frameworks, with optimized context and tool-calling pipelines. Cloud Deployment & CI/CD: Containerized, scalable cloud deployments on AWS/GCP/Azure, memory/context optimization, and continuous delivery of iterative improvements. Rapid Iteration & Measurement: Proof-of-concept to production-grade pipelines with evaluation dashboards to benchmark performance and reliability. I have hands-on experience in building autonomous agents, multi-agent orchestration, and production AI systems with verifiable metrics. GitHub links and technical walkthroughs of past agentic projects are available for review. SEND MESSAGE/CHAT so we can discuss milestones, architecture decisions, and the proof-of-concept swarm you need. Thanks & Regards, Prateek

@ZohaibRoy

⭐⭐⭐⭐⭐ Build Next-Gen Agentic Models for Autonomous Systems ❇️ Hi My Friend, I hope you are doing well. I've reviewed your project requirements and see you are looking for someone to build advanced agentic models. You don’t need to look any further; Zohaib is here to assist you! My team has successfully completed 50+ similar projects focused on AI and automation. I will create scalable systems that integrate state-of-the-art language models and optimize them for real-world tasks. ➡️ Why Me? I can easily handle your project as I have 5 years of experience in AI development, specializing in agentic models, orchestration layers, and cloud deployment. My skills include coding, benchmarking, and optimizing systems. I also have a strong grip on AWS, GCP, and CI/CD processes, ensuring a smooth transition from prototype to production. ➡️ Let's have a quick chat to discuss your project in detail. I’d love to show you samples of my previous work. Looking forward to connecting with you soon! ➡️ Skills & Experience: ✅ AI Development ✅ Cloud Deployment ✅ Agentic Models ✅ Orchestration Layers ✅ Python Programming ✅ AWS/GCP/Azure ✅ Benchmarking ✅ Containerization ✅ CI/CD Pipelines ✅ Memory Optimization ✅ API Integration ✅ Rapid Prototyping Waiting for your response! Best Regards, Zohaib

@rogelitoc

Hello, I can deliver a proof-of-concept swarm that effectively breaks down complex requests, assigns specialized agents, and utilizes a vector store for shared memory. This system will include robust evaluation metrics to track performance and minimize hallucination rates. With over a decade of experience in deploying autonomous agents and orchestrating complex systems, I have successfully transitioned R&D prototypes into production-ready solutions. For instance, I led a project integrating multiple LLMs with LangChain, which improved response accuracy by 30% while optimizing context management. To tackle your project, I’ll architect scalable agentic functions and orchestration layers, focusing on effective memory management and tool-calling pipelines. I’ll leverage AWS for deployment, ensuring robust CI/CD practices are in place for rapid iteration. Could you clarify which specific APIs or external tools need integration? Additionally, do you have preferred frameworks for benchmarking? I’m ready to start immediately and look forward to discussing how I can contribute to your team's vision.

@antonk52

✔✔✔Hold on!! Looking for a Developer Who Gets Results? Hire Me, Relax, and Watch Your Project Turn Into Success✔✔✔ Hello, Before jumping into solutions, I focus on fully understanding the goal of the project and the real problem that needs to be solved. Clear communication and quick feedback are the keys to finishing projects smoothly and on time. I always keep clients updated, share progress frequently, and stay available for real-time discussion when needed. This helps avoid delays and ensures the final result matches expectations perfectly. If you’re looking for someone reliable who treats your project seriously and focuses on delivering results, I’d be happy to discuss the details and get started. Let’s talk and make this project a success. Best Regars Anton

@chiragpipal

Revolutionize your platform with cutting-edge Agentic Models, from autonomous agents to complex orchestrations. With a focus on transitioning R&D prototypes to scalable, mission-critical systems, I bring 5 years of experience and a track record in delivering similar projects offsite. Specializing in architecting and coding large-scale functions, I ensure seamless integration of state-of-the-art language models and optimization for performance and scalability. Let's collaborate on building a proof-of-concept swarm that excels in handling complex requests with precision. Elevate your project to new heights with my expertise in agentic AI solutions. Looking forward to discussing how we can achieve your goals together. Chirag Pipal Regards

@moha262

Hello, I have thoroughly analyzed your project requirements and identified that my core competencies in AI Model Development, AI Research, AI Development, AI Text-to-speech, AI Chatbot Development, AI Agents, AI Text-to-text and AI Model Integration align precisely with your technical specifications. With a decade of specialized experience in this domain, I bring proven expertise in implementing industry-standard methodologies and delivering production-ready solutions. My approach involves: - Technical Assessment: Comprehensive evaluation of project scope, technical constraints, and deliverable requirements - Strategic Planning: Development of detailed implementation roadmap with milestone tracking - Quality Assurance: Rigorous testing protocols and quality control measures throughout the development lifecycle - Timely Delivery: Proven track record of meeting deadlines while maintaining exceptional quality standards I am particularly adept at handling complex technical challenges and implementing scalable solutions that exceed client expectations. My methodology emphasizes precision, efficiency, and adherence to best practices in AI Model Development, AI Research, AI Development, AI Text-to-speech, AI Chatbot Development, AI Agents, AI Text-to-text and AI Model Integration. I would welcome the opportunity to discuss your project's specific technical requirements, timeline expectations, and success metrics in greater detail. Please feel free to schedule a consultation at your

@DngPhgNam

⭐⭐⭐⭐⭐ ✅Hi there, hope you are doing well! I have extensive experience developing autonomous AI agents and complex orchestration systems, having built production-ready multi-agent platforms that coordinate specialized models seamlessly. The most critical part for success here is designing scalable agentic architectures that can reason and plan autonomously while integrating state-of-the-art LLMs efficiently. Approach: ⭕ Architect and implement scalable swarm and orchestration layers enabling autonomous reasoning. ⭕ Integrate and benchmark LLMs like OpenAI, Anthropic, and Llama 2/3 using frameworks such as LangChain. ⭕ Optimize memory sharing and tool pipelines with vector stores for robust execution. ⭕ Deploy cloud solutions with containerization and CI/CD for reliable production readiness. ⭕ Iterate rapidly by shipping, measuring, and refining proof-of-concept swarms with evaluation metrics. ❓ What are your preferred frameworks for agent orchestration beyond those mentioned? ❓ How do you currently measure hallucination and robustness in your prototypes? ❓ Are there specific benchmarks or datasets you'd like to test the swarm performance against? I’m confident in my ability to deliver a high-quality proof-of-concept swiftly and contribute deeply to scaling your agentic AI platform. Best regards, Nam

@hannas62

Hello, As a seasoned AI developer and tutor with extensive experience in building and applying complex scientific models, I believe I possess the necessary skills and mindset to excel in your agentic AI project. My background in materials science and mechanical engineering provides me with a solid understanding of the theoretical underpinnings of AI systems, while my ability to bridge this knowledge with real-world applications ensures that my work is not just academically virtuous but also practically effective. In addition, I am no stranger to importance of high-stakes, mission-critical scenarios - exactly what you are dealing with. Throughout my career, I have not only developed cutting-edge AI models but deployed them to cloud environments, optimized memory capacities and created efficient tool-calling pipelines, all of which are essential requirements for your project. As you cannot spell "Agentic Models" without talented Individual" Furthermore, my commitment to constant improvement and refining resonates well with your team's philosophy of iterative development processes on bleeding-edge concepts. This guarantees that I will invest myself fully in all aspects of your project; from turning R&D prototypes into production-ready systems to scaling up for real-world workloads. I trust that with my Kao chain chopping abilities, I can accomplish your first milestone effortlessly. With me on board, you can be confident that your p Thanks!

@AwaisChaudhry

Hi there, I’m Muhammad Awais, and I’m excited to help you push agentic models from R&D to production. I understand you want a scalable platform that can run single agents, swarms, and complex orchestrations with many LLMs, while keeping memory, context, and tool calls efficient. My approach is to design a modular swarm framework that can reason, plan, and act with minimal human input, then layer in robust benchmarking, memory sharing via a vector store, and clear evaluation metrics for robustness and hallucination. I will integrate leading LLMs and toolkits (OpenAI, Anthropic, Llama families; LangChain, Semantic Kernel, CrewAI or equivalents), optimize CI/CD pipelines, containerize for cloud deployment, and set up observability so we can measure performance and reliability in real time. We’ll ship a proof-of-concept swarm that breaks down a complex request, assigns specialised agents, shares memory, and returns an executable plan with metrics. The plan will be iterated rapidly in tight cycles to reach production readiness and plan for a smooth contractor-to-full-time transition. What is your top priority metric for the PoC: robustness, speed, or scale, and what would be a realistic success threshold? Best regards,