Senior AI Integration Engineer

Role Overview

We are looking for a highly experienced Senior Full-Stack & AI Integration Engineer who thrives at the intersection of modern web technologies, cloud infrastructure, and AI-generated code management. The ideal candidate will be responsible for integrating AI-generated code into our production server environment, maintaining it with robust database architecture, and ensuring long-term scalability and reliability of the system.

Key Responsibilities

AI Code Management: Review, understand, and take full ownership of AI-generated code (from tools such as Claude, Lovable, and similar platforms) — ensuring it meets production standards before and after deployment.

Server-Side Integration: Migrate AI-generated application code onto AWS servers, handling environment setup, CI/CD pipelines, and deployment automation.

Architecture Design: Design, architect, and maintain scalable backend systems that integrate seamlessly with AI-generated frontends and APIs.

API Development: Build and maintain RESTful and GraphQL APIs; ensure reliable communication between frontend interfaces and backend services.

Database Management: Manage and optimize databases (MongoDB, MySQL) — including schema design, query optimization, indexing strategies, and backup processes.

Cloud & DevOps (AWS): Manage AWS infrastructure including EC2, S3, RDS, Lambda, CloudFront, IAM, and related services; implement DevOps best practices.

Frontend Collaboration: Collaborate with frontend teams working in React.js, Node.js, and Angular.js to ensure smooth end-to-end integration.

Code Quality & Review: Establish and enforce code quality standards, review AI-generated code for bugs, security vulnerabilities, and performance bottlenecks.

System Monitoring: Monitor application performance, set up logging and alerting systems, and proactively resolve issues in production.

Documentation: Document architecture decisions, API contracts, and system workflows for team-wide clarity and continuity.

Required Skills & Qualifications

Technical Stack

Server-Side / Backend: Strong proficiency in Node.js, Express.js, Python, or similar server-side technologies

Frontend Frameworks: Hands-on experience with React.js, Angular.js, and Node.js-based frontend pipelines

AI Tools Experience: Working knowledge of Claude (Anthropic), Lovable, GitHub Copilot, or similar AI code generation platforms

Cloud / DevOps: 3+ years of AWS experience — EC2, S3, RDS, Lambda, ECS, CloudWatch, Route 53, IAM

Databases: Proficient in MongoDB (NoSQL) and MySQL (relational); experienced in schema design, indexing, and performance tuning

APIs: Expertise in designing, building, and documenting REST and GraphQL APIs

CI/CD: Experience with pipelines using GitHub Actions, Jenkins, CircleCI, or AWS CodePipeline

Containerization: Familiarity with Docker and Kubernetes for deployment and orchestration

Architecture & Problem Solving

Strong understanding of software architecture patterns — MVC, Microservices, Event-Driven, Serverless

Ability to evaluate, refactor, and optimize code that was auto-generated by AI systems

Knowledge of security best practices — authentication, authorization, data encryption, OWASP standards

Experience with version control (Git) and collaborative workflows (pull requests, code reviews)

Good to Have

Experience with GraphQL and WebSocket-based real-time communication

Familiarity with infrastructure-as-code tools like Terraform or AWS CDK

Knowledge of Redis or other in-memory caching systems

Exposure to AI/ML workflows and LLM API integrations

Prior experience in a startup or fast-paced product environment

Education & Experience

Bachelor's or Master's degree in Computer Science, Software Engineering, or a related field

4–8 years of professional experience in full-stack or backend development

Demonstrated experience working with or maintaining AI-generated codebases is a strong plus