MERN Stack Technical Lead – Cloud & AI Job ID: 417546

The NineHertz; Jaipur; Vor Ort; INR 3.000.000 - 6.000.000; Vollzeit

Zusammenfassung

The NineHertz is seeking a hands-on MERN Stack Technical Lead with 8–12+ years of experience, including 3+ years in technical leadership, to drive architecture, cloud infrastructure, and Generative AI integration for client products.

The role involves close collaboration with product, pre‑sales, QA, DevOps, and UI/UX teams to deliver scalable, secure, production‑grade systems.

Qualifikationen

• Hands-on experience with React.js, Node.js, Express.js, and MongoDB.
• Proficiency in JavaScript and TypeScript, Redux Toolkit, REST APIs, and GraphQL.
• Experience with microservices and event-driven architectures.
• Authentication and authorisation using OAuth 2.0, JWT, and RBAC.
• Real-time applications using Redis and WebSockets.
• Proven experience designing and deploying production applications on AWS or Azure.
• AWS: EC2, Lambda, S3, RDS, ECS/EKS, API Gateway, CloudFront, CloudWatch.
• Azure: App Service, Functions, AKS, Azure SQL, Blob Storage, Azure DevOps.
• Docker, Kubernetes, CI/CD, and Infrastructure as Code.
• Practical experience integrating LLMs / Generative AI into web applications.
• Excellent problem‑solving, communication, and team leadership skills.

Aufgaben

• Lead, mentor, and manage a team of frontend and backend developers.
• Define application architecture, coding standards, and engineering best practices.
• Drive technical decisions and own end‑to‑end delivery of projects.
• Conduct code reviews to ensure code quality, performance, and security.
• Translate business requirements into technical solutions alongside product managers, architects, and stakeholders.
• Design and implement scalable, highly available, fault‑tolerant architectures on AWS, Azure, or GCP.
• Build and maintain CI/CD pipelines using GitHub Actions, GitLab CI/CD, Jenkins, or Azure DevOps.
• Manage containerised workloads with Docker and Kubernetes.
• Provision infrastructure using Terraform or CloudFormation.
• Implement cloud security, IAM, monitoring, logging, backup, and disaster recovery.
• Optimise infrastructure for performance, scalability, and cost.
• Evaluate and integrate LLM services (OpenAI, Azure OpenAI, or similar) into MERN applications.
• Build AI features such as chatbots, intelligent automation, document processing, and RAG pipelines.
• Apply prompt engineering, embeddings, and vector databases to real product use cases.
• Ensure AI implementations follow security, data privacy, and responsible AI practices.
• Lead sprint planning, technical discussions, and architecture reviews.
• Identify technical risks early and resolve complex engineering challenges.
• Ensure timely, high‑quality delivery within Agile/Scrum processes.
• Maintain clear technical documentation.

Kenntnisse

React.js

Node.js

Express.js

MongoDB

JavaScript

TypeScript

Redux Toolkit

REST APIs

GraphQL

Microservices

Event-driven

OAuth 2.0

JWT

RBAC

Redis

WebSockets

AWS

Azure

Docker

Kubernetes

CI/CD

Infrastructure as Code

LLMs / Generative AI

Prompt engineering

Tools

Docker

Kubernetes

CI/CD

GitHub Actions

GitLab CI/CD

Azure DevOps

Terraform

CloudFormation

Jobbeschreibung

About the Opportunity

NineHertz is seeking a hands‑on MERN Stack Technical Lead with 8–12+ years of experience, including 3+ years in technical leadership, to drive architecture, cloud infrastructure, and Generative AI integration for client products. The role involves close collaboration with product, pre‑sales, QA, DevOps, and UI/UX teams to deliver scalable, secure, production‑grade systems.

Role & Responsibilities

• Lead, mentor, and manage a team of frontend and backend developers.
• Define application architecture, coding standards, and engineering best practices.
• Drive technical decisions and own end‑to‑end delivery of projects.
• Conduct code reviews to ensure code quality, performance, and security.
• Translate business requirements into technical solutions alongside product managers, architects, and stakeholders.
• Design and implement scalable, highly available, fault‑tolerant architectures on AWS, Azure, or GCP.
• Build and maintain CI/CD pipelines using GitHub Actions, GitLab CI/CD, Jenkins, or Azure DevOps.
• Manage containerised workloads with Docker and Kubernetes.
• Provision infrastructure using Terraform or CloudFormation.
• Implement cloud security, IAM, monitoring, logging, backup, and disaster recovery.
• Optimise infrastructure for performance, scalability, and cost.
• Evaluate and integrate LLM services (OpenAI, Azure OpenAI, or similar) into MERN applications.
• Build AI features such as chatbots, intelligent automation, document processing, and RAG pipelines.
• Apply prompt engineering, embeddings, and vector databases to real product use cases.
• Ensure AI implementations follow security, data privacy, and responsible AI practices.
• Lead sprint planning, technical discussions, and architecture reviews.
• Identify technical risks early and resolve complex engineering challenges.
• Ensure timely, high‑quality delivery within Agile/Scrum processes.
• Maintain clear technical documentation.

Skills & Qualifications

Must‑Have

• Strong hands‑on experience with React.js, Node.js, Express.js, and MongoDB.
• Proficiency in JavaScript and TypeScript, Redux Toolkit, REST APIs, and GraphQL.
• Experience with microservices and event‑driven architectures.
• Authentication and authorisation using OAuth 2.0, JWT, and RBAC.
• Real‑time applications using Redis and WebSockets.
• Proven experience designing and deploying production applications on AWS or Azure.
• AWS: EC2, Lambda, S3, RDS, ECS/EKS, API Gateway, CloudFront, CloudWatch.
• Azure: App Service, Functions, AKS, Azure SQL, Blob Storage, Azure DevOps.
• Docker, Kubernetes, CI/CD, and Infrastructure as Code.
• Practical experience integrating LLMs / Generative AI into web applications.
• Excellent problem‑solving, communication, and team leadership skills.

Preferred

• Next.js and server‑side rendering.
• LangChain or LlamaIndex.
• Python and FastAPI for AI service integration.
• SaaS and multi‑tenant architecture experience.
• High‑traffic, distributed systems experience.
• Enterprise AI application delivery.
• AWS or Azure Solutions Architect certification.