Location: on-site/remote aligned with European CET/CEST

Reporting to: CTO

Start date: ASAP

At OTee, we’re rethinking industrial automation from the ground up. Our momentum is driven by a clear market need across geographies and a strong support from strategic, international investors. If you've been looking for a place where your work can shape an entire industry (and where you'll feel the energy of real progress every day) this is it. You’ll be joining a lean but growing team that values curiosity, technical excellence, and impact.

💡About the Role

As Lead AI Engineer at OTee, you’ll bridge the gap between Industrial Automation and Artificial Intelligence - two fields that have rarely spoken the same language. You'll build AI-powered features both for our internal dev team and for our product that turn complex automation tasks into something intuitive and intelligent.

You'll own complete features from idea to production. You'll have real autonomy, influence our AI strategy, and help grow the team as we scale. This means working with LLMs, fine-tuning open-source models, integrating commercial AI APIs, and building custom solutions that directly impact how engineers and operators interact with automation systems.

💪 Key Responsibilities

- Own AI Feature Development: Lead the end-to-end development of AI-powered features that extend what engineers can achieve with OTee. Build systems that deliver real intelligence, improve efficiency, and set new standards for performance in industrial automation.

- Drive AI Integration Strategy: Own the integration of LLMs, open-source models, and commercial AI APIs into both internal tools and customer-facing features

- Champion Model Performance & Cost Optimization: Participate in decisions on model selection, fine-tuning strategies, and deployment approaches that balance performance, latency, and cost

- Establish AI Excellence Framework: Create and maintain best practices for prompt engineering, model evaluation, safety guardrails, and quality assurance across all AI initiatives

- Own Production AI Stability: Take end-to-end responsibility for AI system reliability, establishing monitoring strategies for model performance, costs, and user experience

- Build AI Infrastructurre & MCP servers: Design and implement MCP servers and AI infrastructure that extend agent capabilities and enable seamless integration with automation systems

- Drive Cross-Team AI Alignment: Lead technical discussions with product and engineering teams to ensure AI features integrate seamlessly with the broader platform

- Shape AI Technology Evolution: Research and implement emerging AI/ML technologies and techniques that maintain competitive advantage while managing technical complexity

🔎 What We're Looking For

At OTee, we're building a world-class team - and that means we're looking for people who don't just meet the requirements, but exceed them. You should be driven to stay on top of the latest security technologies and methodologies, eager to learn rapidly, and capable of producing high-quality results under evolving demands. This role demands speed, precision, security-first mindset, and a constant hunger for improvement. If you're excited by the idea of setting new standards in secure industrial automation, you'll fit right in.

Education & Experience

- 3+ years of AI/ML engineering experience with production deployments

- Strong proficiency in Python (and optionally Golang)

- Deep understanding of LLMs and transformer architectures

- Solid knowledge of model fine-tuning, prompt engineering, and RAG (Retrieval-Augmented Generation)

- Experience with open-source AI frameworks and commercial AI APIs

- Knowledge of ML model deployment, monitoring, and optimization

- Understanding of AI system architecture and integration patterns

- Experience with cloud platforms and on-premise deployments

- Strong problem-solving and experimentation skills

- Excellent communication and collaboration abilities

(Technical) Skills

- Languages: Python (required), Golang (nice to have)

- AI/ML Frameworks: PyTorch, Hugging Face Transformers, LangChain, vector databases, MCP

- Model Experience: LLM integration, fine-tuning, embeddings, RAG systems

- APIs: Experience with commercial AI APIs and open-source model serving

- Cloud: AWS/GCP/Azure, local/on-premise deployments

- Infrastructure: Docker, Kubernetes, model serving frameworks, AI tooling

- Monitoring: ML model performance tracking, logging, A/B testing

🎯 Personal Qualities

- Ownership of shared responsibility: You feel full responsibility for the AI features you build and ensure all required functionalities are delivered to high quality and in a timely manner, independently and as part of the team

- Collaborative Spirit and Communication: Strong team player with excellent interpersonal skills, working with cross-functional teams and effectively communicating AI concepts to non-technical stakeholders

- Attention to Detail: Meticulous attention to detail, ensuring high-quality AI solutions that adhere to best practices and ethical AI principles

- Problem Solving: Strong analytical and experimental mindset, with the ability to navigate ambiguous AI challenges and create practical solutions

- Adaptability: Comfortable working in a fast-paced, dynamic environment and adapting to evolving AI technologies, changing requirements, and shifting business needs

- Continuous Learning: Passion for staying current with emerging AI/ML technologies, model architectures, and industry developments

- Strategic Thinking: Strong understanding of technical trade-offs and ability to balance model performance, cost, latency, and accuracy with business objectives

- Interest in Industry 4.0: Extra brownie points if you know what a PLC is and are excited about the OT/IT convergence in industrial automation

🤝 What We Offer

- The opportunity to take part in building a product with global impact

- What may be the biggest challenge of your professional career

- A competitive benefits package with stock options

- Being part of an exceptional team, with experts in their respective fields

- An honest work culture where we can admit failures, ask for help and are safe