MERN Stack Technical Lead

Role overview

Technical leadership and architecture

• Lead, mentor, and manage frontend and backend developers.
• Define architecture, coding standards, and engineering best practices; drive technical decisions and project delivery.
• Conduct code reviews and ensure code quality, performance, and security.
• Translate business requirements into technical solutions with product managers, architects, and stakeholders.

Cloud architecture and DevOps

• Design and implement scalable, highly available, fault-tolerant architectures on AWS, Azure, or GCP.
• Build CI/CD pipelines using GitHub Actions, GitLab CI/CD, Jenkins, or Azure DevOps; manage Docker and Kubernetes workloads.
• Provision infrastructure using Terraform or CloudFormation.
• Implement cloud security, IAM, monitoring, logging, backup, and disaster recovery; optimize performance, scalability, and cost.

AI and generative AI

• Evaluate and integrate OpenAI, Azure OpenAI, or similar LLM services into MERN applications.
• Build chatbots, intelligent automation, document processing, and RAG pipelines.
• Apply prompt engineering, embeddings, and vector databases to product use cases while following security, privacy, and responsible AI practices.

Delivery and team management

• Lead sprint planning, technical discussions, and architecture reviews; identify risks and resolve complex engineering challenges.
• Ensure timely, high-quality delivery within Agile/Scrum processes and maintain clear technical documentation.

Requirements

• Experience leading, mentoring, and managing frontend and backend developers.
• Ability to define application architecture, coding standards, and engineering practices.
• Experience designing and implementing scalable cloud architectures on AWS, Azure, or GCP.
• Experience building and maintaining CI/CD pipelines with a listed platform such as GitHub Actions, GitLab CI/CD, Jenkins, or Azure DevOps.
• Experience managing containerized workloads with Docker and Kubernetes.
• Experience provisioning infrastructure with Terraform or CloudFormation.
• Practical experience evaluating and integrating LLM services into applications.
• Ability to apply security, data privacy, and responsible AI practices.