Associate Software Engineer - AI-Augmented Full Stack

Vinove Software; Dadri; On-site; INR 600,000 - 1,000,000; Full time

Job summary

Vinove Software in Noida is seeking an Associate Software Engineer for AI-augmented full-stack development. You will own clearly scoped features from first concept through design interpretation, development, testing, and deployment, shaping user journeys across web interfaces and backend APIs.

Ideal candidates are fresh graduates with strong projects or open-source contributions, eager to learn, own their work, and apply fundamentals of CS to build reliable, production-ready experiences with

Qualifications

• Fresh graduates with strong projects, portfolios, open-source contributions, or demonstrable engineering ability are encouraged to apply.
• Willingness to learn rapidly and take ownership of features.
• Strong fundamentals in computer science and problem solving.

Responsibilities

• Build end-to-end product features from concept to production.
• Translate designs into responsive interfaces and robust APIs.
• Collaborate across frontend, backend, and product teams to deliver value.

Skills

Frontend development

Backend development

Full-stack engineering

AI/ML basics

Job description

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 frameworks and CI/CD
• Familiarity with Docker or cloud deployment
• Experience integrating LLM APIs or building AI-enabled product features
• Evidence that you learned an unfamiliar technology and shipped something useful with it
• Ability to explain technical decisions, compromises, mistakes, and lessons clearly

Certificates alone will not differentiate you. What you have built, how you think, and how quickly you learn will.

This Role May Not Be Right for You If

This position may not be suitable if you:

• Want to work only on AI/ML models or data science notebooks
• Want to work exclusively on frontend or exclusively on backend
• Need complete, step-by-step instructions before beginning
• Treat Figma as something to copy without understanding the user experience
• Depend on AI-generated code that you cannot explain
• Focus only on completing assigned tasks rather than improving the outcome
• Avoid testing, documentation, code review, or feedback
• Are uncomfortable learning unfamiliar technologies

What Success Looks Like

Within your first few weeks, you should be able to understand our engineering standards, development workflow, product context, and existing systems-and begin contributing meaningful improvements.

Within the first 90 days, a successful associate engineer should be able to:

• Independently own a reasonably scoped feature
• Convert a design or workflow into a functional full-stack implementation
• Identify missing requirements and edge cases before development
• Produce clean, reviewable, appropriately tested code
• Use AI tools productively without compromising quality
• Communicate decisions, progress, and risks clearly
• Demonstrate visible improvement in speed, judgement, and engineering maturity

What You Will Get

• Real product ownership from an early stage
• Exposure to frontend, backend, product, design, AI, and deployment
• Opportunities to work on live products and meaningful business problems
• Access to modern AI-assisted engineering tools and workflows
• Mentorship and regular technical feedback
• A high-learning environment with room to experiment
• Career progression based on demonstrated capability and ownership-not merely tenure
• The opportunity to grow into a strong full-stack engineer, product engineer, technical lead, or AI-enabled application engineer