Full Stack SAAS Developer

Full-Stack SaaS Developer – AI, LLMs, Agents & Integrations Contract Type: Long-Term / Ongoing Compensation: $500 USD per month through Upwork and milestones Work Type: Remote We are hiring an experienced Full-Stack SaaS Developer for a long-term role working on an established AI-powered SaaS platform. This is not a frontend-only role or a basic website-development position. You will work across the complete product, including frontend, backend, databases, AI/LLM systems, AI agents, APIs, third-party integrations, cloud infrastructure, CI/CD, testing, performance, and security. We are looking for someone who can understand and take ownership of complete product workflows rather than only individual development tickets. What You Will Work On You will develop, maintain, debug, and improve functionality across areas including: AI agents and agentic workflows LLM-powered product functionality CRM and lead-management systems Customer conversation/inbox systems Lead qualification and scoring Workflow and journey automation Appointment and calendar systems Automated follow-ups Email, SMS, WhatsApp, chat, voice, and social-channel workflows Meta/Facebook/Instagram integrations Google integrations OAuth integrations REST APIs Webhooks Background jobs Real-time functionality Multi-tenant SaaS architecture Authentication and authorization Roles and permissions Subscriptions and feature access Analytics and dashboards Notifications File handling Production deployments Monitoring Application security Performance optimization Required Technical Skills Frontend Strong professional experience with: React JavaScript TypeScript HTML5 CSS3 Modern component-based architecture React Hooks State management API-driven applications Complex forms and validation Authentication flows Role-based interfaces Responsive SaaS dashboards Tables, filters, search, sorting, and pagination Reusable UI components Loading/error/empty states Frontend performance optimization Browser debugging You should understand: Client-side rendering Server-side rendering concepts Lazy loading Code splitting Caching Optimistic UI updates Error boundaries Accessibility fundamentals Backend Strong experience with: Node.js JavaScript / TypeScript backend development C# .NET / ASP.NET Core REST API development Authentication and authorization Middleware Background processing Scheduled jobs Event-driven systems Webhook processing Business logic Validation Error handling Retry mechanisms Idempotency Logging Backend services should be designed to be: Secure Scalable Maintainable Testable Observable Fault tolerant API & Integration Development Required knowledge includes: REST APIs JSON HTTP OAuth 2.0 JWT Refresh tokens Webhooks API keys API authentication Pagination Rate limiting Retry handling Timeout handling Idempotency API versioning Error handling You should have practical experience integrating third-party platforms such as: Meta Graph API Facebook Instagram Google APIs Google OAuth Gmail Google Calendar CRM platforms Communication APIs Voice APIs SMS platforms WhatsApp APIs Email providers Database Engineering Strong PostgreSQL experience is required. You should understand: Relational database design Tables and relationships Primary and foreign keys Indexes Constraints Transactions Joins Views Database migrations Query optimization Database normalization Connection pooling Data integrity Backup/recovery concepts Experience is also required with: Vector databases pgvector or similar technologies Embeddings Similarity search Semantic search Metadata filtering Retrieval systems AI / LLM Engineering You must have practical experience developing AI-powered applications. Required knowledge includes: OpenAI APIs GPT models Claude LLM APIs AI agents Agentic workflows Tool calling Function calling Structured outputs Prompt engineering System prompts Conversation context AI memory Agent state RAG Knowledge bases Vector embeddings Semantic retrieval AI workflow orchestration AI decision logic Guardrails Output validation AI fallback handling Token management LLM latency optimization LLM cost optimization You should understand complete AI workflows such as: User Request → Context → AI Agent → Tool Selection → API Execution → Database Update → Response → Follow-Up Action AI Agent Architecture Required understanding includes: Agent state Tool execution Agent permissions Workflow state Conditional actions Human-in-the-loop workflows Scheduled actions Follow-up logic Retry logic Escalations Failure handling Long-running workflows Duplicate-action prevention Real-Time Systems Required understanding of: WebSockets Server-Sent Events Live notifications Real-time inboxes Chat systems Event-driven UI updates SaaS Architecture You should have experience working with production SaaS applications involving: Multi-tenancy Tenant isolation Organizations/workspaces Users Teams Roles RBAC Permissions Feature gating Subscription plans Usage limits User invitations Audit logs Activity logs Account settings Account lifecycle Onboarding flows Software Architecture Required knowledge includes: Clean architecture Separation of concerns Modular architecture Service layers Reusable services Dependency management SOLID principles DRY principles Design patterns Domain/business logic Refactoring Technical debt management Existing/legacy codebase maintenance You should be comfortable understanding and improving an existing production codebase rather than unnecessarily rebuilding functionality. Git & GitHub Strong experience required with: Git GitHub GitHub CLI Branching Pull requests Code reviews Merge conflicts Rebasing Cherry-picking Commit history Rollbacks Releases Tags GitHub Actions Expected workflow: Branch → Develop → Test → Review → Pass CI → Merge → Deploy → Verify CI/CD & DevOps Required experience with: GitHub Actions CI/CD pipelines Automated builds Automated testing Linting Type checking Security checks Deployment pipelines Staging environments Production environments Rollbacks Environment variables Secrets management A feature is not considered complete simply because it works locally. Cloud Infrastructure Required experience with: Microsoft Azure Vercel Cloud deployments Environment configuration Production/staging environments DNS fundamentals SSL/TLS Database hosting Cloud storage Serverless concepts Monitoring Scaling Testing & QA Developers are expected to test their own work. Required understanding includes: Unit testing Integration testing API testing End-to-end testing Regression testing Manual testing Edge-case testing Authentication testing Permission testing Webhook testing Database testing Integration testing You should be comfortable identifying: Reproduction steps Expected behavior Actual behavior Root causes Regression risks Debugging Strong debugging ability is essential. You should be able to trace issues across: Frontend → API → Backend → Database → Third-Party Integration → AI Agent → Infrastructure You should be comfortable using: Browser DevTools Network inspection Application logs Server logs Database queries API responses Stack traces Monitoring systems Git history We expect root-cause fixes rather than temporary patches. Security Security knowledge is required. You should understand: OWASP principles Secure authentication Authorization RBAC Tenant isolation OAuth security JWT security API security Webhook verification Input validation SQL injection prevention XSS prevention CSRF protection CORS Secure cookies Rate limiting Brute-force protection Secure headers Password security Encryption in transit Encryption at rest Secrets management API-key protection Database security Secure file uploads Sensitive-data handling Secure logging Credentials, API keys, customer data, tokens, and environment secrets must never be exposed in client-side code, repositories, logs, or error responses. Performance & Reliability Required understanding includes: Frontend performance Backend performance Database optimization API latency Query optimization Caching Pagination Lazy loading Background processing Connection pooling Memory usage Application bottlenecks Retry strategies Exponential backoff Timeout handling Error recovery Idempotency Race conditions Concurrent processing Duplicate-event prevention Monitoring & Observability You should understand: Application logging Error tracking Performance monitoring API monitoring Database monitoring Health checks Deployment monitoring Audit logging Structured logging Production issues should be diagnosable through data and logs rather than guesswork. AI-Assisted Development Our engineering workflow uses modern AI development tools. You should be comfortable with: Claude ChatGPT / GPT OpenAI Codex GitHub CLI AI-assisted code review AI-assisted debugging AI-assisted testing AI-generated code must still be reviewed, understood, tested, and secured by the developer responsible for shipping it. What We Expect We want a developer who thinks like a full-stack product engineer. For example, a workflow may involve: Social Message → Webhook → Contact Identification → CRM Record → AI Agent → Conversation Context → AI Decision → API/Tool Execution → Appointment → Follow-Up → Database Update → Activity Log → Dashboard Update You should be capable of understanding, developing, testing, and debugging the complete workflow. We expect: Strong ownership Clear communication Independent problem solving Root-cause analysis Clean and maintainable code Security awareness Product thinking Attention to edge cases Good Git discipline Self-testing before handoff Protection against regressions Documentation of important technical decisions Who Should Apply Apply if you have professional experience with most or all of the following: Production SaaS products React Node.js C# / .NET PostgreSQL Vector databases AI/LLM systems AI agents CRM functionality APIs and webhooks OAuth Meta integrations Google integrations Multi-tenant SaaS Azure Vercel GitHub GitHub Actions CI/CD Testing Security Production debugging Contract & Compensation This is intended to be a long-term Upwork engagement. Budget: $500USD/month All communication before the contract and all payments will remain through Upwork in accordance with Upwork's platform requirements. No unpaid trial work or free development tasks are required. Application Questions Please include the following in your Upwork proposal: Briefly describe 2–3 production SaaS products you have worked on. What specifically did you personally build in those products? Describe your experience with React and Node.js. Describe your C#/.NET experience. Describe your PostgreSQL experience. Have you worked with pgvector or another vector database? What AI/LLM applications have you built? Have you built AI agents with tool/function calling? Which Meta APIs have you implemented? Which Google APIs or OAuth integrations have you implemented? Describe your Azure and Vercel experience. Describe your experience with GitHub Actions and CI/CD. What is your approach to testing your own development work? Describe your application-security experience. Describe one difficult production SaaS bug you personally solved. What was the root cause, how did you identify it, and how did you verify the fix? Are you available for a long-term monthly engagement? Please do not include personal email addresses, phone numbers, WhatsApp, Telegram, or other off-platform contact details in your proposal. We will conduct pre-contract communication through Upwork.