Full Stack Engineer — AI-Enabled Application Development

Location: Chennai, India; Madurai, India

Department: Engineering Team

Experience: 3-6 yrs

About the Role

Key Responsibilities

• Design, develop and deliver full stack applications end-to-end across backend (Java / .NET / Python / Node.js) and frontend (React / Angular) stacks.
• Use AI coding assistants and LLM-based tooling as a first-class part of the development workflow — from prototyping to production-grade code.
• Apply prompt engineering best practices and spec-driven development to translate business requirements into clear specs, then into AI-assisted implementations.
• Refactor and modernize legacy codebases — improve structure, testability, performance and maintainability without breaking behavior.
• Contribute to solutioning and architecture discussions: evaluate trade-offs, pick the right stack, and apply appropriate design patterns.
• Work flexibly across more than one project at a time, context-switching cleanly between domains and tech stacks.
• Coach and mentor junior engineers on coding standards, AI-assisted workflows, debugging, and design thinking.
• Participate in code reviews, technical estimations, and quality engineering practices (unit tests, CI/CD, observability).

Must-Have Qualifications

• 3–6 years of professional full stack development experience shipping production applications.
• Strong hands-on coding ability in at least two of: Java (Spring Boot), .NET (C# / ASP.NET Core), Python (Django / FastAPI / Flask), Node.js.
• Proficient with at least one modern frontend framework — React or Angular — including state management, component design and REST/GraphQL integration.
• Demonstrable experience using AI coding assistants (e.g., Claude, GitHub Copilot, Cursor, ChatGPT) to design, generate, refactor and review code in real projects.
• Working knowledge of prompt engineering best practices: context setting, role prompts, decomposition, examples, evaluation, and guarding against hallucination.
• Experience with spec-driven / specification-first development — turning requirements into clear specs, acceptance criteria and AI-executable instructions.
• Solid grasp of OOP, SOLID, common design patterns (factory, strategy, repository, adapter, etc.) and clean architecture principles.
• Proven track record of refactoring existing codebases — identifying smells, breaking down monoliths, improving test coverage and reducing tech debt.
• Comfort with relational and NoSQL databases, REST APIs, authentication/authorization, and basic cloud deployment (AWS / Azure / GCP).
• Version control (Git), CI/CD pipelines, and disciplined engineering practices.
• Strong communication skills — able to explain technical ideas to engineers and non-engineers alike.

Good to Have

• Experience building or integrating with LLM APIs, RAG pipelines, vector databases, or agentic frameworks.
• Familiarity with evaluation and testing practices for AI-generated code (golden tests, snapshot tests, eval harnesses).
• Exposure to micro-frontends, microservices, event-driven architectures or DDD.
• Containerization (Docker), orchestration (Kubernetes), and infrastructure-as-code.
• Open-source contributions or technical writing / public speaking.

How You Work

• Comfortable juggling more than one project and switching context without dropping quality.
• Curious about new tools, especially in the AI / developer-tooling space, and quick to adopt what works.
• Generous with knowledge — you enjoy pairing with and coaching younger engineers.
• Bias for action, with a habit of breaking ambiguous problems into shippable increments.

What We Offer

• Opportunity to work on diverse projects across multiple stacks and domains.
• A culture that treats AI-assisted development as a core engineering competency, not a side experiment.
• Mentorship-driven team where coaching others is recognized and rewarded.
• Competitive compensation and growth path into senior / lead engineering roles.

How to Apply