Artificial Intelligence Engineer

Job description – AI Engineer

The Mission

We're not looking for someone who just knows AI — we're looking for someone who can build with

it. 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. We need someone

who can go end-to-end: from database to frontend to deployed AI feature.

We're Assisted-First Coders — And We Thrive In It

Let's be upfront: we use AI to code. Cursor, Copilot, Claude, ChatGPT — whatever gets the job

done faster and better. We don't gatekeep productivity behind write every line yourself purity. We

believe the best engineers in 2026 are the ones who know how to think, what to build, and how to

leverage AI as a force multiplier to get there.

But here's the thing — assisted-first doesn't mean clueless-first. You still need to understand what

the code is doing, why an architecture decision matters, and when the AI is giving you garbage.

We use AI to move at 3x speed, not to skip understanding. If that's how you already work — or

how you want to work — you'll fit right in.

What You'll Be Doing

Building AI-Powered Products

• Build and ship full-stack features with AI/agentic capabilities baked in

• Develop AI agents, automation workflows, and intelligent backends

• Work with LLMs, prompt engineering, and tool-use patterns in production contexts

• Own prototypes end-to-end — from concept to working deployment

Engineering & Architecture

• Work across the stack — APIs, databases, frontend, cloud infra

• Help design scalable, clean architectures (bonus if you've touched multi-tenant systems)

• Write production-quality code, not just scripts — whether you wrote it or your AI pair did

Research & Experimentation

• Stay current with Generative AI and Agentic AI developments

• Evaluate new tools, frameworks, and models for practical use

• Participate in brainstorming and technical design discussions

What We're Looking For

Must-Haves

• Minimum 1 year of professional experience as an AI Engineer — building and

shipping LLM/AI-powered features in real products (this is not a fresher role)

• You've built and shipped at least one full-stack application end-to-end in a professional

setting (MERN, PERN, Django, FastAPI, Next.js — stack doesn't matter, the builder

mindset does)

• Solid Python or JavaScript/TypeScript fundamentals• Strong understanding of AI/ML concepts and production experience with LLMs, prompt

engineering, and tool-use/agent patterns

• Logical thinking and ability to break down a problem into a working system

• Comfort with Git, REST APIs, and databases (SQL or NoSQL)

Great to Have

• Experience with multi-tenant architectures or SaaS product development

• Familiarity with cloud platforms (AWS, GCP, or Azure)

• Exposure to tools like LangChain, CrewAI, or similar agentic frameworks

• Prior work with authentication, role-based access, or any real-world system design

challenge

• Deployed and maintained applications in production

• Already comfortable using AI coding assistants as part of your workflow

Mindset

• Builder first. You default to making things, not just studying them.

• Assisted-first, not dependent. You use AI tools aggressively but understand what's

happening under the hood.

• Comfortable with ambiguity — you figure things out

• Takes ownership. Doesn't wait to be told every step.

Eligibility

• Minimum 1 year of full-time professional experience in an AI Engineer role —

freshers will not be considered

• Degree in CS, IT, AI, or related field (or equivalent practical experience)

• Professional experience in full-stack development (required)

• Proven AI/ML work in production, such as LLM integrations, AI agents, or automation

pipelines (required)

What You'll Gain

• Work directly with the Founder/CEO and CTO on live products

• Hands-on experience building AI-powered applications from scratch

• Exposure to startup product building, cloud infra, and go-to-market

• A strong track record in applied AI

• Clear growth path with increasing ownership and responsibility based on performance

• Fast-paced environment with real ownership and freedom to experiment

Who Should Apply

• You've spent at least a year working as an AI Engineer and want to keep building

intelligent products

• You care about shipping, not just learning

• You use AI tools daily and want to work somewhere that encourages it — not frowns on it

• You're excited about AI as a tool inside products, not just as a research topic