I’m ready to kick-off a SaaS project that delivers a scalable, cloud-hosted AI Resume Optimization Platform and have it live no later than January 1, 2026. The first release focuses on one core feature—resume analysis and feedback—yet it must be built on architecture that lets us expand into job matching, multilingual support, and other modules over time. Key capabilities I need in the initial build: • Automated resume analysis and feedback that covers: – Grammar and spelling checking – Content optimization against a supplied job description – Formatting and layout improvement • English-language processing today, but the codebase should be structured so additional languages slot in with minimal rework. • Secure, multi-tenant cloud deployment (AWS or comparable) with strong authentication, role-based access, and encrypted data at rest and in transit. • Efficient, well-documented AI pipelines—think Python, LangChain, or similar—optimised for quick inference and low operating cost. • Responsive web interface (React or Vue preferred) plus REST/GraphQL endpoints so we can expose services to future mobile clients. • Performance monitoring, logging, and basic analytics baked in from day one. What I’ll consider a successful hand-off: 1. A deployable codebase in a private Git repo, with CI/CD scripts and infrastructure-as-code (Terraform or CloudFormation). 2. Staging environment up and running in my cloud account. 3. Technical documentation that walks through architecture, data flow, and how to add new languages. 4. A two-hour knowledge-transfer call and 30 days of post-launch bug support. Experience building SaaS products, working with AI/NLP toolchains, and squeezing maximum performance out of cloud resources is a must. If you’re available to start immediately and can commit to steady progress through the next milestones, let’s talk.