INUA AI

Computers + 1 more

AI Full Stack Application Developer

Job details

Contract Type

Description

We are seeking a Frontend Developer skilled in AI-assisted development using Lovable.dev to rapidly build React applications from natural language prompts. You’ll refine AI-generated code—fixing logic issues, architecting state management with React Hooks, and ensuring clean, maintainable components. The ideal candidate has deep React expertise, strong JSON/API integration skills, and the ability to bridge AI-generated output with production-quality frontend code.


Required Qualifications

  • Experience developing SaaS applications sold to business customers, including multi-tenant architecture and subscription billing integrations.
  • Background in cybersecurity tooling security dashboards, compliance platforms, vulnerability management UIs, or training applications.
  • Familiarity with LangChain, LlamaIndex, RAG architectures, or vector databases (Pinecone, pgvector).
  • Experience with Terraform or AWS CDK for infrastructure-as-code.
  • AWS Certified Developer or Solutions Architect certification.
  • Knowledge of security compliance frameworks: SOC 2, NIST CSF, ISO 27001


Responsibilities
  • Design, develop, and maintain full-stack web applications across the company’s commercial product portfolio.
  • Build new customer-facing features and internal tools using AI-assisted development workflows (Claude Code) as a core part of the development process.
  • Own AWS infrastructure for hosted applications including ECS/Fargate, Lambda, S3, RDS/Aurora, CloudFront, and related services ensuring reliability, scalability, and security.
  • Develop and maintain RESTful and GraphQL APIs that power front-end experiences and integrate with third-party security tools.
  • Implement front-end interfaces using React or Next.js, ensuring responsive, accessible, and performant UIs for business and end-user customers.
  • Support and extend current applications in production, triaging bugs, improving performance, and managing releases.
  • Integrate AI/ML capabilities including LLM APIs, AI-generated content pipelines, and intelligent automation into product features.
  • Collaborate with security, product, and training teams to understand requirements and translate them into shipped software.
  • Establish and maintain CI/CD pipelines (GitHub Actions or equivalent) for automated testing, building, and deployment to AWS.
  • Participate in code reviews, architectural discussions, and sprint planning; help define engineering best practices across the team.
  • Ensure all applications meet security standards: secure coding practices, authentication/authorization (OAuth 2.0, SAML/SSO), encryption at rest and in transit.


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