AI-Native Full Stack Engineer | AI Agents, Automations & Integrations

I run a growing business and have been using AI tools to improve how we build software, manage information, and handle day-to-day operations. I've experimented with Claude, ChatGPT, AI coding assistants, custom GPTs, and workflow automations. Some of these experiments are working well, while others are half-built, disconnected, or need proper engineering before I can rely on them. I'm looking for a hands-on AI-native full-stack engineer who can help me turn these experiments into practical, reliable solutions. Someone who can move between writing code, connecting systems, building AI-powered workflows, and identifying opportunities to eliminate repetitive manual work. I don't need someone who simply prompts AI to generate code. I need someone who understands what they're building, knows how the pieces fit together, and can take ownership from the initial idea through testing, deployment, and documentation. What you'll work on 1. AI-Native Full Stack Development Build and improve applications using Python, Django, Django REST Framework, React, and TypeScript. Design APIs, database schemas, data models, and backend services that can scale with the business. Use AI coding tools such as Claude Code, GitHub Copilot, Cursor, or similar tools to accelerate development. Review, test, debug, and validate AI-generated code before it reaches production. Build integration tests, automated test suites, and reliable CI/CD workflows. 2. AI Agents and Workflow Automation Build AI-powered workflows that connect LLMs, APIs, databases, webhooks, and third-party applications. Develop agentic workflows for tasks such as document processing, information extraction, research, reporting, and internal operations. Use orchestration, structured outputs, validation, retries, and error handling to make automations dependable. Work with tools such as n8n, Make, Power Automate, or custom Python-based automation when appropriate. Identify repetitive manual tasks and turn them into measurable, maintainable workflows. 3. AI Tools and Business Integrations Configure and improve Claude, ChatGPT, custom GPTs, Microsoft 365 Copilot, or Copilot Studio where relevant. Integrate AI solutions with business applications, cloud services, and existing systems. Build retrieval-based solutions using RAG, embeddings, vector search, or document-processing pipelines where needed. Help organize business knowledge so AI tools can retrieve the right information from approved sources. Work with SharePoint, Microsoft 365, document libraries, permissions, and knowledge bases when the project requires them. 4. Architecture, Reliability, and Production Evaluate existing prototypes and decide what should be improved, rebuilt, deployed, or discontinued. Design service boundaries, asynchronous processing, queues, event-driven workflows, and safe retry mechanisms where appropriate. Investigate failures, API limitations, data inconsistencies, performance issues, and integration problems. Deploy and maintain applications on AWS, Azure, or comparable cloud platforms. Document technical decisions, provide clear handover notes, and record short walkthroughs so the team can maintain what you've built. What I'm looking for Strong hands-on experience with AI-assisted software development and practical AI automation. Solid Python skills, ideally with Django and Django REST Framework. Strong React and preferably TypeScript experience. Experience designing and integrating REST APIs, webhooks, databases, and third-party services. Practical experience building LLM-powered applications, AI agents, or multi-step automated workflows. Understanding of orchestration, structured data, failure handling, retries, and human approval steps where necessary. Experience with relational databases such as PostgreSQL or MySQL, including schema design and query optimization. A disciplined approach to testing, security, code review, and production readiness. The ability to understand a business problem, recommend a sensible solution, and explain technical decisions in plain English. Nice to have Claude Code, Cursor, GitHub Copilot, ChatGPT, and custom GPT development. Microsoft 365, SharePoint, Copilot Studio, and Power Automate. n8n, Make, LangChain, LangGraph, or comparable orchestration tools. RAG, vector databases, OpenSearch/Elasticsearch, and document intelligence. AWS, Azure, Docker, CI/CD, and automated testing. Experience with B2B SaaS, internal business tools, or operational workflow modernization. Experience working with sensitive business data and access-control requirements. How we'll work together I'd prefer to start with a small, paid trial project. We'll review an existing workflow, prototype, or business process, identify what needs fixing or building, and agree on a practical scope. I'll be looking for someone who can demonstrate working solutions, explain their architecture, identify limitations, and deliver something the business can actually use. A short technical assessment, a clear written recommendation, and a walkthrough of the finished work will be part of the process. This could develop into ongoing work for the right person as we identify more opportunities to improve our systems and operations. To apply Please include: Two or three relevant projects you've personally built, preferably involving AI agents, full-stack applications, or business automation. A brief explanation of your role in each project, including the tools and integrations you implemented. One example of a workflow or application where you used AI coding tools but still took responsibility for testing, debugging, and production readiness. Your preferred approach to a paid trial project. I'm more interested in what you've actually built and how you think through problems than in a long list of tools on your profile.