Artificial Intelligence Engineer

About Onified.ai

At Onified.ai, we're building the world's first Enterprise Resource Intelligence (ERI) platform.

Our vision is to move beyond traditional enterprise software by bringing together enterprise applications, Industry 4.0, AI and Agentic AI into a single AI-native platform.

We're developing 50+ integrated enterprise applications across Manufacturing, Supply Chain, Finance, HR, Projects, Governance, Sustainability and more, with AI built into the platform rather than added as an afterthought.

The Opportunity

We're looking for an AI Engineer (0–3 years) who has a strong foundation in AI/ML and, more importantly, loves building things with it.

This is not a role where you need to arrive knowing every new AI framework. The field is changing too quickly for that.

But you do need the fundamentals.

You should already understand AI/ML concepts, be comfortable programming in Python, and have actually built AI/ML projects through academics, internships, research, personal projects or professional work.

From there, we'll help you go deeper.

You'll get the opportunity to work hands-on with Generative AI, LLMs, RAG, agents, enterprise data and emerging AI technologies and learn how to take AI from experimentation to real enterprise products.

We'll invest in your learning, but we're looking for people who have already made a serious start.

What You'll Build

Depending on the problem, you could work on:

• AI agents and Agentic AI workflows
• Enterprise copilots and intelligent assistants
• Retrieval-Augmented Generation (RAG)
• Enterprise search and knowledge systems
• Document intelligence
• Natural-language interfaces for enterprise data
• AI-powered workflow automation
• Recommendations and decision support
• Multimodal AI applications
• Evaluation, guardrails and reliability of AI systems

What You Must Have

For this role, these are essential:

• Strong Python programming fundamentals
• Understanding of core Machine Learning concepts, supervised/unsupervised learning, training, validation, overfitting, metrics, feature engineering, etc.
• Understanding of Generative AI and Large Language Models (LLMs)
• Hands-on AI/ML project experience through academics, internships, research, personal projects or professional work
• Ability to work with data using libraries such as NumPy and Pandas
• Exposure to ML frameworks such as scikit-learn, PyTorch or TensorFlow
• Basic understanding of APIs, databases and Git
• Strong logical, analytical and problem-solving ability

A relevant degree or coursework in Computer Science, AI, Machine Learning, Data Science, Mathematics, Statistics, Engineering or a related quantitative field is preferred.

Strong candidates from other academic backgrounds are welcome if they can demonstrate equivalent AI/ML knowledge and hands-on work.

Good to Have

You don't need to know all of these. We'll help you learn many of them:

• RAG, embeddings and semantic search
• AI Agents / Agentic AI
• Prompt engineering and structured outputs
• LangChain, LangGraph or LlamaIndex
• MCP (Model Context Protocol)
• Vector databases / pgvector
• FastAPI
• PostgreSQL
• Open-source LLMs
• Model evaluation and AI testing
• Docker
• AWS or other cloud platforms

What Matters to Us

We're not looking for someone who has simply completed a few AI tutorials.

We're looking for someone who is technically grounded, curious and loves experimenting and building.

Maybe you've trained your own ML models. Maybe you've built a RAG application, experimented with open-source models, created an AI agent, worked on a research project, or built something completely different.

We'd like to see it.

Your experience can be academic, personal or professional. What matters is that you've gone beyond learning the theory and actually tried to make AI work.

Why Join Onified.ai

You won't be joining to maintain one ML model or spend your first year waiting for meaningful AI work.

You'll have the opportunity to work across real enterprise problems and explore how AI can fundamentally change the way businesses operate.

You'll get to:

• Build real AI products from the beginning
• Work with LLMs, agents, RAG and emerging AI technologies
• Experiment and prototype new ideas
• Work with complex enterprise data and workflows
• Take ideas from prototype towards production
• Learn alongside Product, Engineering and domain teams
• Develop rapidly as the AI landscape evolves

We can teach you our stack, frameworks and approaches. We can't teach curiosity, problem-solving ability or the desire to build.

Bring the fundamentals and the mindset. We'll help you build depth.

Interested

If you already have a solid AI/ML foundation and you're excited by the idea of building things that haven't been built before, we'd like to hear from you.

Show us what you've built.

Projects, GitHub repositories, research, internships and experiments all count.

Come build the future of Enterprise Resource Intelligence (ERI) with us.