[Internal Hiring]: Product-Associate Software Engineer – AI-Augmented Full Stack

Job Description

Associate Software Engineer – AI-Augmented Full Stack

Department: Product Engineering

Employment Type: Full-Time

Experience: 0–2 Years

Location: Noida – Work from Office

Exceptional freshers with strong projects, portfolios, open-source contributions, or demonstrable engineering ability are encouraged to apply.

Build Products, Not Just Tickets

We are looking for an unusually capable early-career software engineer who wants to become a world-class product builder.

You should be able to start with a product problem, competitor reference, rough workflow, wireframe, or Figma design—and help transform it into a thoughtful, polished, reliable, production-ready feature.

This role combines:

• •Full-stack software engineering
• •Frontend and UI craftsmanship
• •Backend and database development
• •Product and workflow thinking
• •UI/UX understanding
• •Competitive research
• •AI-augmented development
• •Rapid learning and experimentation

You will not be limited to writing code against perfectly documented requirements. You will be expected to understand what is being built, why it matters, how leading products solve similar problems, what users may struggle with, and how the overall experience can be improved.

AI should make you faster and more capable. It should not replace your judgement, fundamentals, or ownership.

This is not an AI/ML research role, a passive trainee position, or a ticket-execution role. It is a high-growth engineering opportunity for someone with strong fundamentals, exceptional curiosity, and the ambition to become an outstanding full-stack product engineer.

What You Will Do

Build end-to-end product experiences

Own clearly scoped features from understanding the problem through design interpretation, development, testing, deployment, and improvement.

You may work on product applications, internal platforms, customer-facing workflows, websites, dashboards, automation systems, integrations, and AI-enabled product capabilities.

Turn Figma into production-quality interfaces

Translate Figma designs and wireframes into responsive, accessible, high-performance frontend experiences.

You will be expected to:

• •Build reusable components rather than one-off screens
• •Maintain design consistency across pages and workflows
• •Handle desktop, tablet, and mobile behaviour
• •Think through loading, empty, error, success, validation, permission, and edge-case states
• •Identify inconsistencies or usability gaps in the design before blindly implementing them
• •Balance visual fidelity with usability, performance, maintainability, and accessibility

Build reliable backend systems

Design and implement the backend capabilities required to support product experiences, including:

• •APIs and service logic
• •Database schemas and queries
• •Authentication and permissions
• •Validations and error handling
• •Third-party integrations
• •Background jobs and notifications
• •Logging, monitoring, and basic security controls

You should be able to understand the complete data flow—from user action in the interface to backend processing, storage, and response.

Understand the product before coding

Before implementation, understand:

• •The user’s objective
• •The business objective
• •The existing workflow
• •The desired outcome
• •Dependencies and constraints
• •Possible failure points
• •Edge cases and alternate paths

You may be required to map workflows, propose wireframes, clarify acceptance criteria, identify missing states, or recommend a simpler approach before development begins.

Conduct meaningful competitive analysis

Study how relevant products solve similar problems and identify:

• •Common workflow patterns
• •User experience conventions
• •Strengths and weaknesses
• •Missing capabilities
• •Opportunities for simplification or differentiation

Competitive analysis is not about copying another product. It is about understanding the market, learning from established patterns, and making informed product decisions.

Use AI throughout the engineering lifecycle

Use modern AI coding assistants, agents, and language models to accelerate:

• •Technical research
• •Prototyping and scaffolding
• •Code generation
• •Debugging
• •Refactoring
• •Test creation
• •Documentation
• •Code review
• •Competitive research
• •Understanding unfamiliar codebases or technologies

However, you must understand, validate, test, and take responsibility for everything you submit.

We do not want engineers who copy AI-generated code without understanding it. We want engineers who use AI to explore more alternatives, learn faster, reduce repetitive work, and produce better outcomes.

Learn new technologies quickly

You may occasionally be required to work with a framework, API, library, platform, or development approach that you have not used before.

You should be comfortable learning from documentation, examples, existing code, experimentation, and AI-assisted research—and converting that learning into working software.

Maintain a high engineering standard

Write code that is:

• •Clear and understandable
• •Modular and maintainable
• •Secure by design
• •Appropriately tested
• •Easy for another engineer to review
• •Consistent with the existing architecture
• •Suitable for production use

Participate constructively in code reviews and improve your work based on feedback.

What We Are Looking For

Engineering fundamentals

You should have a sound understanding of:

• •Programming fundamentals
• •Data structures and basic algorithms
• •Object-oriented and/or functional programming concepts
• •APIs and client-server architecture
• •Relational or document databases
• •Version control using Git
• •Debugging and problem isolation
• •Basic application security
• •Testing principles

We value practical understanding over memorised terminology.

Frontend capability

Hands-on experience with:

• •HTML
• •CSS
• •JavaScript or TypeScript
• •Responsive web development
• •A modern frontend framework such as React, Next.js, Vue, or Angular
• •Component-based development
• •API integration
• •Browser debugging and performance basics

You should care about spacing, hierarchy, typography, responsiveness, interaction states, and the overall quality of the user experience.

Backend capability

Working knowledge of at least one backend technology or ecosystem, such as:

• •Node.js
• •Python
• •Java
• •.NET

You should understand how to build APIs, work with databases, validate inputs, handle errors, structure application logic, and implement basic authentication and permissions.

You do not need to be equally advanced across every layer on day one. However, you must be willing and able to work across the complete stack.

Product and UI/UX thinking

You should be able to look beyond the visible screen and think about:

• •User journeys
• •Information hierarchy
• •Workflow simplicity
• •Form behaviour
• •Navigation
• •Feedback and system states
• •Accessibility
• •Error prevention
• •Edge cases
• •Business rules

Formal design training is not required, but sensitivity to good product design is essential.

Learning ability and ownership

We are looking for someone who:

• •Learns quickly and independently
• •Asks thoughtful questions
• •Investigates before escalating
• •Can work through ambiguity
• •Does not wait passively for every detail
• •Accepts feedback without becoming defensive
• •Communicates progress and blockers clearly
• •Takes responsibility for the final outcome, not merely the code written

What Will Make You Stand Out

You will have a significant advantage if you can demonstrate one or more of the following:

• •A strong GitHub profile or product portfolio
• •A complete application that you built and deployed
• •Meaningful open-source contributions
• •Experience converting Figma designs into responsive interfaces
• •Experience designing both frontend and backend for the same feature
• •Experience with design systems or reusable component libraries
• •Knowledge of PostgreSQL, Redis, queues, caching, or search
• •Experience with testing fram