AI Low-Code Developer (Rapid Prototyping + Fast MVP Delivery) to $2200

Mission of the Role

To quickly and reliably create prototypes and MVPs (web apps, internal tools, AI agents workflows), using low-code/no-code and AI-assisted development, bringing them to deployment, monitoring, and clear support.

Key Tasks

• Quickly assemble prototypes and MVPs: UI, logic, integrations, data storage, authorization, basic analytics.
• Make AI-assisted coding the standard: code generation, refactoring, tests, documentation, development acceleration.
• Translate business needs into requirements: user flows, roles, edge cases, constraints, acceptance criteria.
• Integrate external services: CRM, payments, email/SMS, messengers, webhooks, partner APIs.
• Design a simple but correct MVP architecture: so it doesn't fall apart under the first load.
• Set up deployment and environments: dev/stage/prod, secrets, domains, SSL, basic CI/CD.
• Establish observability: logging, basic monitoring, alerts, error tracking.
• Participate in task estimation: timelines, risks, trade-offs (fast vs. correct), release plan.

What We Consider Success (KPI / Outcomes)

• MVP in production in 2-6 weeks (depending on scale) with working key scenarios.
• Reduction in development time due to AI tools (visible increase in speed and quality).
• Minimum blocker bugs at launch, transparent logs, and reproducibility.
• Clear artifacts: brief PRD/BRD-lite, technical description, deployment, and support instructions.

Mandatory Requirements (must-have)

• 2+ years in prototype/MVP development or a strong portfolio with real launches.
• Ability to work in conditions of uncertainty: formulating requirements together with the business.
• Understanding of business processes and business analysis skills: asking the right questions, documenting processes, identifying bottlenecks.
• Confident work with APIs, webhooks, databases (SQL/NoSQL), auth (JWT/OAuth), queues, or their substitutes.
• Understanding of deployment and operation: Docker (preferred), cloud deploy, environment variables, secrets, domains.
• Experience using AI development tools as a daily practice.