Overview

Sr. Full Stack Engineer (Agentic AI + MERN)

Responsibilities

• Design, build, and scale high-quality web applications using MongoDB, Express.js, React.js, and Node.js.
• Own features end-to-end, from technical design and architecture through implementation, testing, deployment, and production support.
• Design and develop robust, secure, and scalable RESTful APIs and integrations with internal and third-party services.
• Contribute to system architecture, technical design decisions, scalability, reliability, and performance optimization.
• Build modular, reusable, maintainable components and services following strong software engineering principles.
• Diagnose and resolve complex production and performance issues through structured debugging and root-cause analysis.
• Write clean, testable, production-grade code and actively contribute to code reviews, engineering standards, and automated testing.
• Collaborate closely with Product, Design, QA, DevOps, and other engineering teams to deliver high-impact solutions.
• Evaluate emerging technologies and identify opportunities to improve developer productivity, system performance, and product capabilities.
• Explore and contribute to AI-powered product capabilities, including LLM integrations, AI agents, prompt engineering, and AI-assisted engineering workflows.

Qualifications

• 4–8 years of professional software engineering experience, with strong hands-on expertise in the MERN stack.
• Deep practical knowledge of JavaScript/TypeScript, Node.js, React.js, MongoDB, and Express.js.
• Strong understanding of REST API architecture, authentication, authorization, security, error handling, and API performance.
• Solid understanding of data structures, algorithms, object-oriented/programming fundamentals, and problem-solving.
• Demonstrated ability to design scalable, modular, maintainable, and resilient systems.
• Strong debugging and analytical skills with an ability to break down ambiguous technical problems into practical solutions.
• Strong understanding of software development lifecycle and experience working in collaborative engineering environments.
• A strong ownership mindset—you take responsibility for quality, reliability, and outcomes, not just implementation.
• LLM application development
• Agentic AI / AI agents
• LangChain or similar agent frameworks
• Prompt Engineering
• Tool/function calling and structured outputs
• RAG and vector databases
• AI-assisted coding and developer workflows
• Building AI-powered features into existing applications
• Evaluating and improving LLM-based systems
• TypeScript expertise
• GraphQL
• WebSockets / real-time application development
• Microservices and distributed systems
• AWS, Azure, or GCP
• Docker and Kubernetes
• Redis, queues, caching, or event-driven architectures
• TDD and automated testing frameworks
• Observability, monitoring, logging, and performance engineering
• Think beyond the ticket and understand the larger product and technical context.
• Can challenge assumptions and make sound engineering trade-offs.
• Care deeply about code quality, scalability, performance, and maintainability.
• Are comfortable taking ownership of technically challenging problems.