AI Engineer — Build & Deliver AI Systems for Real Businesses

@devendrathakur12

Hello, I've delivered almost this exact kind of work across both tiers — SMB n8n/Notion/Pinecone RAG agents and enterprise LangChain on Azure OpenAI with Azure AI Search. Tier 1: I build RAG pipelines end to end (chunking, embedding, retrieval), route models via OpenRouter, store vectors in Pinecone or Supabase pgvector, and deploy Slack bots plus HubSpot/Intercom integrations on DigitalOcean. Tier 2: LangChain/LlamaIndex in Python, containerised in Docker, Bedrock/Azure OpenAI, Weaviate or Azure AI Search, Teams bots, and SharePoint/Confluence indexing, monitored via Datadog. I work async from a brief and can jump on client calls. I'll send two production examples across both tiers. Best, Dev S.

@ZohaibRoy

⭐⭐⭐⭐⭐ Build Reliable AI Solutions for Businesses with Proven Expertise ❇️ Hi My Friend, I hope you're doing well. I've reviewed your project requirements and see you're looking for an experienced developer for your AI consultancy. Look no further; Zohaib is here to help you! My team has successfully completed over 50 projects in AI systems and automation. I will ensure we create effective AI audits, knowledge bases, and automation layers that meet your needs without requiring constant supervision. ➡️ Why Me? I have over 5 years of experience in AI solutions, specializing in both Tier 1 and Tier 2 delivery. My skills include n8n workflow orchestration, Notion for knowledge management, and deploying AI agents. I also have a strong grip on Azure services, Docker, and ensuring security protocols are followed strictly. ➡️ Let's have a quick chat to discuss your project in detail. I can share samples of my previous work that demonstrate my capabilities. I'm looking forward to discussing this with you! ➡️ Skills & Experience: ✅ n8n Workflow Orchestration ✅ Notion Knowledge Base ✅ OpenRouter Model Routing ✅ Pinecone/Supabase Vector DB ✅ RAG Pipelines ✅ Slack Bot Deployment ✅ DigitalOcean Hosting ✅ LangChain / LlamaIndex ✅ Azure OpenAI / AWS Bedrock ✅ Docker & Container Services ✅ Azure API Management ✅ Strong Written Communication Waiting for your response! Best Regards, Zohaib

@corpmember29

Hello, I have carefully reviewed your AI Engineer requirement and fully understand the need for a reliable long-term technical partner who can independently architect, build, and deliver production-ready AI systems for SMB and enterprise clients. I RECENTLY WORKED ON SIMILAR AI AUTOMATION, RAG PIPELINE, AI AGENT, AND ENTERPRISE INTEGRATION PROJECTS AND I CAN SHARE PORTFOLIO, ARCHITECTURE EXAMPLES, AND RELEVANT WORK SAMPLES DURING DISCUSSION. With 10+ years of experience in AI engineering, backend systems, and cloud infrastructure, I have hands-on production experience across both Tier 1 and Tier 2 environments including n8n, LangChain, LlamaIndex, OpenRouter, Pinecone, Supabase pgvector, Azure OpenAI, AWS Bedrock, Docker, Teams/Slack bots, SharePoint indexing, and enterprise-grade RAG pipelines. I am comfortable working asynchronously from briefs, handling secure deployments, implementing strict credential management workflows, and building scalable AI orchestration systems with clean documentation and maintainable architecture. WE WILL WORK WITH AGILE METHODOLOGY, PROVIDE CLEAN PRODUCTION-READY CODE, 2 YEARS FREE ONGOING SUPPORT, AND ASSIST FROM ARCHITECTURE TO FINAL DEPLOYMENT. I am available for long-term collaboration and client-facing technical discussions when required. Thanks Christina

@mobiwebsolutions

✋ Hi There!!! ✋ THE GOAL OF THE PROJECT:- TO DESIGN AND BUILD SCALABLE AI SYSTEMS INCLUDING RAG PIPELINES ORCHESTRATION LAYERS AND ENTERPRISE GRADE AI AGENTS FOR REAL BUSINESS ENVIRONMENTS. I have carefully read requirement for building production AI solutions across SMB and enterprise stack including n8n LangChain vector databases and secure deployments. I can deliver stable and scalable AI systems from brief with minimal guidance. I am best fit due to strong hands on experience in end to end AI engineering and automation platforms. 1 RAG pipelines with vector databases like Pinecone and Supabase for knowledge based AI systems 2 workflow orchestration using n8n and LangChain for automation and system integration 3 enterprise deployment with Docker Azure OpenAI AWS and secure secrets management practices I will provide UI design, database management, testing, and full source code delivery at project completion plus deployment and documentation. I have 9+ years experience as full stack and AI systems developer. I have delivered similar AI agent and enterprise automation projects. Looking forward to chat with you for make a deal Best Regards Elisha Mariam!

@neerajdhameliya

Hello, This is exactly the type of role I’m looking for, long-term, real business deployments, and full ownership of technical delivery. I’ve built production AI systems across both SMB and enterprise environments using n8n, LangChain, RAG pipelines, Pinecone/pgvector, OpenRouter, Azure OpenAI, Docker, Slack/Teams bots, and enterprise knowledge indexing. What stood out to me is your “2nd Brain” approach. I’ve worked on several systems where disconnected business knowledge was transformed into searchable AI infrastructure powering agents and automation. I work independently, communicate clearly, and take security seriously from day one. What industries are most of your current clients in? Best, Niral

@goranm16

Hi, The risk here isn’t building a few bots — it’s ending up with fragile demos that can’t survive client data, permissions, security reviews, or handover. Your real product is a repeatable AI delivery system: audit → knowledge capture → RAG layer → orchestration → agents, with enough structure to work for SMBs and enterprise clients without rebuilding every engagement. I can help build this as a clean delivery stack: - RAG pipelines with proper chunking, metadata, permissions, and retrievable audit trails - n8n/LangChain orchestration that is documented and easy to hand over - Notion, SharePoint, Confluence, HubSpot, Intercom, and similar system indexing - secure deployment with scoped access, secrets management, and client-environment data boundaries One example: if old emails, files, and owner knowledge are dumped into a vector DB without source permissions, the agent may expose the wrong information. I’d solve that with connector-level scoping, metadata filters, and clear offboarding steps from day one. My plan would be to standardize the build templates first, then create reusable ingestion, retrieval, workflow, and agent modules so each new client delivery is faster and safer. Happy to start with one brief and turn it into the first production-ready client system. Best,

@ivicab6

Hi, I've built AI solutions for a range of clients, from SMBs to enterprises, focusing on n8n for workflow orchestration and RAG pipelines for knowledge management. I’ve delivered AI audit reports, set up searchable knowledge bases, and automated tasks with n8n workflows. If you need a reliable partner to align with your vision and deliver production-ready systems, let’s chat about your first project. Best Regards, Ivica

@rbtech1984

Hello There!!! ★★★★ ( End-to-end AI systems engineer for RAG, agents, and enterprise automation workflows ) ★★★★ Project understanding: You are running an AI consultancy and need a long-term engineer to build production-ready systems across SMB and enterprise tiers. Work includes AI audits, RAG-based “2nd brain” knowledge systems, orchestration via n8n/LangChain, and deployment of AI agents integrated with Slack, Teams, and business tools, with strict security and scalable architecture. ⚜ RAG pipelines with vector DBs (Pinecone, pgvector, Weaviate) ⚜ n8n + LangChain workflow orchestration systems ⚜ AI agent development (Slack, Teams, HubSpot, Intercom) ⚜ Knowledge base “2nd Brain” architecture design ⚜ Azure OpenAI / AWS Bedrock integrations ⚜ Dockerized enterprise AI deployments ⚜ Secure secrets management & compliance-first design I have built AI automation systems and LLM-based pipelines with focus on retrieval, agent workflows and API integrations. I am comfortable working independently from briefs and shipping production-ready systems. My approach is to design scalable RAG architecture first, then build orchestration layer and deploy agents with secure, observable infrastructure. lets connect and discuss your first client engagement. Warm Regards, Farhin B.

@ShaikhAneesa

Hi there, I understand you need a long-term technical partner who can independently architect and deliver production-grade AI systems across both SMB and enterprise environments, while you focus on client strategy and relationships. My approach will be to structure engagements around modular AI architecture using n8n, LangChain/LlamaIndex, vector databases such as Pinecone, pgvector, or Azure AI Search, and model-agnostic routing through OpenRouter, Azure OpenAI, or Bedrock depending on client requirements. I can build searchable “2nd Brain” systems using Notion, SharePoint, Confluence, and enterprise document indexing, then deploy Slack or Teams-based AI agents with orchestration workflows, retrieval pipelines, and API integrations across tools like HubSpot, Intercom, and Xero. Security and deployment standards will follow scoped-access principles, containerized infrastructure, secrets management, and cloud-native isolation for enterprise clients. The deliverable will include production-ready AI systems, documented deployment architecture, orchestration workflows, RAG pipelines, secure integrations, and maintainable infrastructure aligned with both SMB and enterprise standards. Are your current engagements weighted more toward rapid SMB delivery using n8n/Notion stacks, or toward enterprise Azure/AWS environments where governance and infrastructure requirements dominate architecture decisions? I’m ready to start immediately. Warm Regards, Aneesa.

@codeandcommand

Working with mid-market and PE-backed clients means AI systems need to work in production, not just demo well. I build with LangChain, Azure OpenAI, Claude, and n8n, and I know how to wire them into messy real-world data and workflows. What does a typical engagement look like for you? Custom agents, workflow automation, or data pipelines? I can start today and have a first working system ready within a week. Bid and timeline are opening estimates. Real numbers after we walk through the first scope together.

@adriank06

This sounds like a solid operation. Managing the gap between a clean brief and a secure, production-ready AI system is where most consultancies stall. I’ve built exactly what you’re describing—RAG pipelines on Notion for SMBs and Azure-hosted agents for enterprise. The biggest challenge here isn’t the code; it’s ensuring the "2nd Brain" stays fresh without manual upkeep while keeping data locked in their Azure/VPC perimeters. I handle this by chaining automated ingestion triggers with strict RBAC in secrets managers, so agents only "see" what they’re authorized to. I’m comfortable with both the n8n/LangChain stack and the strict security protocols you listed. Let’s hop on a quick call to see if my background matches your current pipeline needs. Are you free Thursday afternoon?

@dushyant317

We’re experienced in building production-grade AI systems across both SMB and enterprise environments, including RAG pipelines, vector databases, multi-model orchestration, n8n/LangChain automation, Slack & Teams agents, and secure cloud-native deployments. We work comfortably from async briefs, prioritize clean architecture and security-first engineering, and can deliver scalable AI infrastructure that integrates seamlessly with client systems and existing workflows.

@DMarian13

Hello, This role fits my background well. I’m a Full Stack SaaS Engineer with strong experience building AI-enabled SaaS platforms, backend APIs, automation workflows, integrations, RAG-style knowledge systems, and production deployments. I can support you as the technical delivery partner behind your consultancy: taking briefs and turning them into working systems without constant hand-holding. Relevant experience: - n8n workflows, webhooks, API integrations, and LLM automation - RAG pipelines: ingestion, chunking, embeddings, retrieval, and AI response layers - Supabase/PostgreSQL, pgvector-style workflows, MongoDB, Node.js/NestJS, Python - Slack/internal bots, customer-facing AI assistants, dashboards, and SaaS portals - Docker, AWS/VPS deployment, GitHub workflows, secure API architecture - Production systems involving payments, webhooks, order flows, background jobs, and monitoring My usual approach: 1. Review the client brief, systems, data sources, and security limits. 2. Build the knowledge ingestion/vector search layer. 3. Connect orchestration through n8n, LangChain-style flows, or backend APIs. 4. Deploy AI agents for Slack/Teams/chat/customer workflows. 5. Add documentation, monitoring, and clean handover notes. I’d be happy to start with one internal prototype or client workflow, then continue as a long-term retainer partner.

@dataspro

Hello! I have a strong background in AI engineering and a proven track record of developing AI systems for real-world applications. I am excited about the opportunity to contribute my technical skills to your project and help deliver impactful solutions. Looking forward to potentially collaborating with you on this exciting venture!

@invoketech

Hi, I’m Jitendra from Invoke Tech. I’ve reviewed your requirements and this aligns directly with the kind of production AI systems we build for clients—RAG-based knowledge systems, workflow orchestration, and enterprise-grade agent deployments. I have hands-on experience across both Tier 1 and Tier 2 stacks: n8n automation, Supabase/pgvector and Pinecone-based RAG pipelines, OpenRouter routing, Slack/Teams agents, and DigitalOcean deployments, as well as enterprise implementations using LangChain, LlamaIndex, Azure OpenAI, Weaviate, Dockerized services, and Azure-native search and monitoring setups. I’ve built “2nd Brain” systems, internal AI copilots, and multi-system orchestration layers for operational automation. Security-first design is standard in my work—secrets management, scoped API access, data isolation, and cloud-native deployment practices aligned with enterprise compliance expectations. I can plug into your consultancy as a reliable delivery partner, working independently from briefs to ship production-ready systems across SMB and enterprise environments with clean architecture, clear documentation, and long-term maintainability. THANKS INVOKE TECH

@Feriver

Hello, I understand you're building an AI consultancy delivering production-grade systems across SMB and enterprise clients, including AI audits, 2nd Brain RAG knowledge bases, orchestration workflows, and AI agents integrated with Slack, Teams, and core business systems. This role requires real production experience across Tier 1 and Tier 2 stacks, with strong focus on reliability and security. I can design and deliver end-to-end solutions using n8n, Notion, OpenRouter, Pinecone/Supabase/Weaviate, and LangChain/LlamaIndex. I have built RAG pipelines including chunking, embedding, retrieval, and evaluation, along with workflow automation and AI agent deployments. On the enterprise side, I work with Azure OpenAI, AWS Bedrock, Dockerized services, API gateways, and observability tools, ensuring systems run securely within client environments. I work independently from briefs, ship production-ready systems, and prioritize secure architecture (secrets management, scoped access, no local data storage, and compliant handling of client data). I can also help standardize your architecture into reusable templates to scale delivery across multiple clients efficiently. Thanks, Asif

@sebastiang076

⭕ Hello, Client ⭕ With my 7+ years of experience and specialization in AI-powered applications, SaaS platforms, and scalable MVP development, I bring a rich skill set that aligns perfectly with your project needs. Over the years, I have successfully built AI systems similar to what you've described - including AI-Powered Applications, Chatbots, and Automation Tools. In particular, I'm well-versed with both the Tier 1 and Tier 2 requirements that you've outlined and have a proven production experience across them - not just limited to tutorials or demos. The deployment, hosting, and snapshot deployments with DigitalOcean are second nature to me. My startup-focused approach allows me to see beyond just the technology to function as a product owner. Given the overarching theme of your project - reliable delivery without hand-holding - my clean and scalable code along with my dedication to delivering quality applications could be a great asset for you. Further assuring you of my commitment to security, I have a solid grasp of data protection obligations (including Australian Privacy Act) and abide by rigorous security practices like managing all credentials in dedicated secrets manager and avoiding storage of raw client data on personal devices. Best Regards,

@sjohn117

Hi, I'm Sean, a Full-Stack Developer with over 10 years of experience, specializing in AI systems and workflow automation. I understand that you need a reliable partner to build robust AI solutions for established businesses and mid-market companies. My experience in deploying scalable AI agents, RAG pipelines, and workflow orchestration using n8n perfectly aligns with your project requirements. Additionally, I have successfully integrated AI technologies like LangChain and Notion into existing systems, ensuring efficient data connectivity and knowledge management. I focus on developing clean, maintainable code with thorough documentation and testing. My approach emphasizes security, ensuring compliance with standards such as the Australian Privacy Act, while managing credentials securely via dedicated secrets management. I can deliver the first working milestone within one week, establishing a strong foundation for our long-term collaboration. How do you envision the collaboration process for this long-term engagement? Best regards, Sean

@dorofiip

Hey, I can start now. ✅I’ve worked on something very similar. Building AI systems for real businesses can be challenging, especially when working on long-term retainers. What really matters here is delivering reliable solutions without constant guidance. In my previous projects, I've built AI systems for various businesses, including developing AI agents and implementing workflow orchestration with tools like n8n and Notion. While I haven't done the exact same project, I have experience in deploying AI solutions and ensuring data security compliance within client environments. Let's chat! -Dorofii