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.

@dinotech

Hi There, Hope you are doing good. I have read the scope of work and I think both of us can do a great partnership. Technical side and client side technical meetings we can handle. I have a dedicated team working on AI solution. So on business end you can manage and at technical end I can manage. Both Tier 1 and Tier 2 solutions we can made in both web and mobile. To start we are ready to do a demo for you so you check our work quality. Let's start with a quick chat. Looking forward to hear from you. Thanks

@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

@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

@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

@extreamcode

Hi, As an AI Engineer with over 15 years of robust experience in full-stack development, network engineering, and AI tool creation, I am confident that I can be a considerable asset to your team. My skills span both Tier 1 and Tier 2 environments as required for this project. With exposure to platforms like n8n, Notion, OpenRouter, Pinecone, Supabase pgvector, Slack bots and more on the SMB side; coupled with working on LangChain, Azure OpenAI, Azure API Management and the like on enterprise projects - my familiarity in these areas is extensive. Such versatility makes me adept at adapting to your specific project needs across varying business scales with competence. Moreover, with security being non-negotiable in accessing client systems for your project; rest assured that I regard it with utmost importance. I consistently manage credentials and API keys via a dedicated secrets manager as well as abide by the perspective of minimizing data exposure to personal devices. As an engineer experienced in handling all facets of software creation - from planning to post-launch support - you can rely on me to contribute not only strategically but also toward effective execution. What sets me apart is an overarching vision for my work that focuses not just on development but also on deployment and support coverage after completion. In addition to reliable skill sets across your required technologies, I'll bring clear communication, pract Thanks!

@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,

@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.

@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

@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

@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.

@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.

@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!

@omard211

You handle the client side. You need someone who can take a brief and actually ship the four deliverables without you checking the work. Most engagements live or die on the 2nd Brain. If the RAG retrieval is weak, the agents on top of it feel useless and the client notices fast. So I start there. Clean chunking, embeddings that match the content, retrieval tested against real queries before anything gets deployed. Then the orchestration layer connects their systems and the agents go live against a knowledge base that actually works. I have shipped both tiers. n8n, Pinecone, and Slack bots for smaller clients. LangChain, Azure OpenAI, and Teams bots for enterprise. On security I keep keys in a secrets manager, use scoped read-only access, and keep client data off personal devices. Enterprise data stays in their cloud. Happy to jump on calls when a client needs reassurance.