Senior AI Engineer

At Supermodular AI, we believe AI is revolutionizing the way people and organizations work—making teams more efficient and focused on what truly drives success. We partner with IT organizations to develop tailored AI Agents that seamlessly integrate into enterprise workflows, automate complex tasks and accelerate business outcomes. Our approach is not about adding more tools but about embedding AI into the systems IT professionals already use, ensuring automation and intelligence align with their unique challenges. From DevOps and cloud migration to cybersecurity and business continuity, our Agents address the most critical pain points by learning from the organization and evolving with its needs. Though we are a young company, our team has a proven track record in building high-impact AI solutions and scaling engineering teams. With our first clients already benefiting from our technology, we are on a fast-growth trajectory to redefine how IT harnesses AI. Join us if you’re excited to work in a high-paced, impact-driven environment where AI is not just a tool but a game-changer for real companies. If you thrive on solving complex problems and want to shape the future of intelligent automation, Supermodular AI is the place for you!

Your Role

As a Senior AI Engineer at Supermodular AI, you will take ownership of the AI/ML domain, shaping how intelligence is designed, trained, evaluated, and deployed across our products. You’ll work with large language models (LLMs), embeddings, retrieval systems, classifiers, and other ML techniques to power the AI agents that our enterprise customers rely on. You will be responsible for both experimentation and productionization: designing robust pipelines for model training, building evaluation frameworks, and ensuring models are reliable, performant, and aligned with customer needs. You’ll collaborate with our engineering leads on architectural decisions, while also working with product teams to translate complex AI capabilities into real-world business outcomes. This is a role for someone who thrives on end-to-end ownership of AI systems—balancing research with pragmatic engineering, and mentoring junior colleagues to raise the bar of our AI practice.

Desired skills and qualifications

• Proven experience working with modern AI/ML techniques, including large language models (LLMs), embeddings, retrieval systems, evaluation methods, and classifiers.
• Hands‑on expertise in at least one major ML/AI framework (e.g., PyTorch, TensorFlow, JAX) and proficiency with Python for prototyping and production code.
• Strong understanding of evaluation strategies for AI systems, including quantitative metrics and qualitative analysis, to ensure performance and reliability.
• Practical knowledge of key concepts in applied ML, such as prompt engineering, fine‑tuning, RAG (retrieval‑augmented generation), and supervised/unsupervised learning.
• Experience building and deploying machine learning systems at scale, including data pipelines, model serving, and monitoring.
• Ability to make architectural decisions that balance experimentation, scalability, and maintainability.
• Experience mentoring and collaborating with more junior AI/ML engineers, fostering best practices in research and development.
• Strong communication and collaboration skills to work cross‑functionally with engineering, product, and business stakeholders.
• Founder mindset —makes informed decisions with cost/speed/value in mind and is comfortable navigating uncertainty or less‑than‑clear requirements.

Job type: full‑time

Selection process

• Online application: Share your CV and any relevant resource to impress us.
• First‑round interview: Let's get to know each other better with an informal chat.
• Second‑round interview: Deep‑dive on your technical skills with a little challenge.
• Offer: Sort out the last details and join the team!