Senior AI Integration Engineer

Bent Chair; Delhi; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

Bent Chair, located in Delhi, is seeking a highly experienced Senior Full-Stack & AI Integration Engineer. This role involves integrating AI-generated code with a focus on maintaining database architectures and ensuring long-term scalability. Candidates should have 4-8 years of professional experience, strong proficiency in Node.js and AWS, and the ability to manage AI-generated codebases. This position also requires designing and optimizing APIs, and collaboration with frontend teams working in React.js and Angular.js.

Qualifications

• 4–8 years of professional experience in full-stack or backend development.
• Strong proficiency in server-side technologies like Node.js and Express.js.
• Experience managing AI-generated codebases is preferred.

Responsibilities

• Integrate AI-generated code into production server environments.
• Design and maintain scalable backend systems.
• Build and maintain RESTful and GraphQL APIs.

Skills

Node.js

Express.js

Python

React.js

Angular.js

AWS

MongoDB

MySQL

REST APIs

GraphQL

Education

Bachelor's or Master's degree in Computer Science

Tools

GitHub Actions

Docker

Kubernetes

Job description

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.