AI Engineer

Location: Noida, NCR
Experience: Minimum 1 Year
Type: Full-Time

About Klypup

Klypup is an AWS Partner and a digitally native cloud services company helping businesses leverage the power of AI and AWS. As a growing startup focused on building intelligent, AI-powered products and solutions, we’re looking for engineers who want to build, experiment, and create real-world impact.

At Klypup, AI doesn’t live in a notebook. It lives inside real products — full-stack applications, automation pipelines, and intelligent systems that businesses actually use.

As an AI Engineer, you’ll work directly with the Founder/CEO and CTO to build and ship AI-powered applications, develop intelligent automation workflows, and take ownership of projects from concept to production. We’re looking for hands-on builders who understand both AI and full-stack engineering and know how to turn ideas into working products.

Your Mission

AI-Powered Product Development

• Build and ship full-stack applications with AI and agentic capabilities.
• Develop AI agents, automation pipelines, and intelligent backend systems.
• Integrate Large Language Models (LLMs) into real-world applications.
• Apply prompt engineering, tool-use patterns, and agent workflows to solve business problems.
• Build functional prototypes and take them from concept to production deployment.
• Identify opportunities to use AI to improve existing products, workflows, and business processes.
• Focus on building practical, reliable, and scalable AI-powered solutions.

Full-Stack Engineering & Architecture

• Develop end-to-end applications across frontend, backend, APIs, and databases.
• Build and maintain REST APIs and backend services.
• Work with SQL or NoSQL databases to design and manage application data.
• Develop frontend interfaces and integrate them with backend services and AI capabilities.
• Contribute to clean, scalable, and maintainable software architecture.
• Work with authentication, role-based access control, and application security where required.
• Support the development of multi-tenant architectures and SaaS applications.
• Write production-quality code, whether developed independently or with AI coding assistants.

AI, LLMs & Agentic Systems

• Work with LLMs, generative AI, and agentic AI technologies.
• Design and implement AI workflows that use tools, APIs, and external data sources.
• Experiment with different models, prompts, frameworks, and approaches to improve performance.
• Evaluate AI-generated outputs and ensure that implementations are reliable and fit for purpose.
• Understand the limitations of AI models and develop appropriate validation and error-handling mechanisms.
• Explore frameworks such as LangChain, CrewAI, and similar agentic AI tools.
• Stay updated with developments in generative AI and identify opportunities to apply them to real products.

Cloud, Deployment & Production Engineering

• Deploy and maintain AI-powered applications in production environments.
• Work with cloud platforms such as AWS, Google Cloud Platform (GCP), or Microsoft Azure.
• Integrate AI services with existing applications, databases, and cloud infrastructure.
• Troubleshoot application issues and improve performance, reliability, and scalability.
• Use Git and version control best practices for collaborative development.
• Understand the complete application lifecycle, from development and testing to deployment and maintenance.
• Contribute to building reliable systems that can support real-world business requirements.

AI-Assisted Development & Innovation

• Use AI coding assistants such as Cursor, GitHub Copilot, Claude, and ChatGPT to accelerate development.
• Leverage AI tools to improve coding speed, debugging, research, testing, and problem-solving.
• Review, validate, and understand AI-generated code before integrating it into applications.
• Make sound technical decisions instead of relying blindly on AI-generated suggestions.
• Evaluate new AI development tools and frameworks for practical implementation.
• Participate in technical brainstorming, architecture discussions, and product experimentation.
• Continuously improve development workflows by combining strong engineering fundamentals with AI-assisted coding.

What We’re Looking For

Experience

• Minimum 1 year of full-time professional experience as an AI Engineer.
• Proven experience building and shipping AI- or LLM-powered features in real-world products.
• Experience developing and deploying at least one full-stack application end-to-end in a professional setting.
• Hands-on experience integrating LLMs, AI agents, or intelligent automation workflows into applications.
• Practical understanding of moving AI prototypes into working, production-ready solutions.
• Experience working with frontend, backend, APIs, and databases.
• Freshers without the required professional experience will not be considered.

Core Technical Skills

• Strong fundamentals in Python or JavaScript/TypeScript.
• Solid understanding of AI/ML concepts and generative AI.
• Practical experience with LLM integrations and prompt engineering.
• Understanding of AI agents, tool calling, and agentic workflows.
• Experience with at least one full-stack technology stack, such as MERN, PERN, Django, FastAPI, or Next.js.
• Familiarity with REST APIs and application integration.
• Working knowledge of SQL or NoSQL databases.
• Proficiency with Git and version control.
• Ability to debug, test, and maintain application code.

Engineering & Problem-Solving Skills

• Ability to break down complex problems into practical, working systems.
• Understanding of software architecture, clean code, and maintainability.
• Ability to evaluate technical trade-offs and make informed implementation decisions.
• Strong logical reasoning and analytical thinking.
• Ability to understand and validate AI-generated code rather than accepting it blindly.
• Comfortable working across different layers of an application.
• Ability to take ownership of a feature from initial idea through deployment.
• Willingness to learn new technologies and adapt to evolving project requirements.

Preferred Experience

• Experience building SaaS products or working with multi-tenant architectures.
• Familiarity with cloud platforms such as AWS, GCP, or Azure.
• Experience with agentic AI frameworks such as LangChain, CrewAI, or similar tools.
• Experience with authentication, authorization, and role-based access control.
• Exposure to production deployments and application maintenance.
• Experience integrating third-party APIs and external services.
• Familiarity with AI-assisted development tools such as Cursor, GitHub Copilot, Claude, or ChatGPT.
• Experience working in a startup or fast-paced product development environment.

Mindset & Working Style

We’re looking for engineers who are builders first.

• Builder first: You enjoy creating working products rather than only studying technologies or building isolated demos.
• AI-assisted, not AI-dependent: You use AI tools to accelerate development while understanding the code, architecture, and decisions behind the output.
• Ownership-driven: You take responsibility for your work and move tasks forward without waiting for step-by-step instructions.
• Comfortable with ambiguity: You can work through unclear requirements, explore solutions, and make progress independently.
• Experimentation-oriented: You are curious about new technologies and enjoy testing practical ideas.
• Product-minded: You think beyond code and consider how your work solves actual business problems.

Eligibility

• Minimum 1 year of full-time professional experience in an AI Engineer role.
• A degree in Computer Science, Information Technology, Artificial Intelligence, or a related field, or equivalent practical experience.
• Professional full-stack development experience is required.
• Proven hands-on experience with AI/ML in production, including LLM integrations, AI agents, or automation pipelines, is required.
• Strong fundamentals in at least one programming language, preferably Python or JavaScript/TypeScript.
• Freshers and candidates without the required professional experience will not be considered.

Application Requirements

Please include:

• An updated resume highlighting relevant professional experience and technical skills.
• Links to GitHub repositories, portfolios, or relevant projects, where available.
• Details of at least one full-stack application you have built and shipped professionally.
• Examples of AI-powered applications, LLM integrations, agents, or automation workflows you have implemented.
• A brief explanation of your role, technical contributions, and the challenges you solved.
• Details of any applications you have deployed or maintained in production.

What We Offer

Career & Growth

• Work directly with the Founder/CEO and CTO on live products.
• Take ownership of AI-powered applications from concept to deployment.
• Gain hands-on experience building intelligent products and automation systems.
• Develop expertise across AI engineering, full-stack development, and cloud infrastructure.
• Grow into roles with increasing technical ownership and responsibility based on performance.
• Contribute to product and architectural decisions as the team grows.

Learning & Innovation

• Work with modern generative AI and agentic AI technologies.
• Use AI coding assistants as an integral part of your development workflow.
• Experiment with emerging models, frameworks, and development tools.
• Gain exposure to cloud infrastructure, SaaS product development, and production engineering.
• Learn by solving real-world technical and business challenges.
• Build a strong portfolio of applied AI engineering experience.

Culture

• Founder-led, fast-paced startup environment.
• Freedom to experiment, explore, and propose new ideas.
• A culture that values practical execution, ownership, and continuous learning.
• Opportunities to work across the full technology stack.
• A focus on shipping useful products rather than building demos that never reach production.

Bonus Points

We’d love to see candidates with:

• Hands-on experience building AI agents that interact with tools and APIs.
• Experience shipping LLM-powered features to real users.
• Experience building and deploying SaaS applications.
• Familiarity with AWS services and cloud-based AI deployments.
• Experience with multi-tenant systems or complex application architectures.
• A strong GitHub portfolio or examples of independently built applications.
• Experience using AI coding assistants effectively in day-to-day development.
• A track record of taking projects from an initial idea to a deployed product.

Success Milestones

First 3 Months

• Understand Klypup’s products, architecture, and development workflows.
• Contribute to existing full-stack applications and AI-powered features.
• Build and ship assigned features using AI-assisted development practices.
• Demonstrate strong ownership, code quality, and problem-solving ability.

First 6 Months

• Independently deliver AI-powered features from concept to production.
• Develop or improve AI agents and automation workflows.
• Contribute to application architecture, integrations, and deployment processes.
• Identify opportunities to improve development speed, product functionality, and reliability.

First 12 Months

• Own the development of significant AI-powered product features or applications.
• Contribute to scalable, production-ready AI and full-stack systems.
• Drive experimentation and implementation of useful AI technologies.
• Take increasing responsibility for technical decisions, delivery, and product outcomes.

Klypup is an Equal Opportunity Employer.

Build with AI. Ship real products. Make an impact.

Category: Engineering / Artificial Intelligence

Type: Full-Time

City: Noida

Country: India

Travel: As required by business needs