Staff AI Engineer

About Clarity AI

Clarity AI is a global tech company founded in 2017 with a unique mission: bringing societal impact to markets. We leverage AI and machine learning technologies to provide top international investors, governments, companies, and consumers with the right data, methodologies, and tools to make more informed decisions. We are now a team of more than 300 highly passionate and curious individuals from all over the world, with offices in New York, Madrid, London, Paris, and Abu Dhabi. Together, we have established Clarity AI as a leading sustainability tech AI company backed by investors and strategic partners such as BlackRock, SoftBank, and Deutsche Börse, who believe in us and share our goals. We are dedicated to cultivating an exceptional workplace environment, and we take pride in our culture, defined by our commitment to being fact-based, diverse, transparent, meritocratic, and flexible.

About The Role

We are looking for a Staff AI Engineer who thrives at the intersection of rapid experimentation and agile product development. In this role, you will be the bridge between the latest AI developments and tangible product impact. You aren't just following a roadmap; you are helping define it by proving what is possible with the latest frontier models and architectures. You will be responsible for the "quality loop": moving from a promising proof-of-concept to a highly reliable, optimized, and validated product.

What You’ll Be Doing

• Product-Centric Development: Designing and executing experiments to improve GenAI capabilities. This isn't just about "accuracy" in a vacuum—it's about optimizing for user value, reliability, and cost-effectiveness.
• Evaluation Systems: Building the "Golden Path" for quality. You will design and implement robust, multi-dimensional evaluation suites (e.g., using "LLM-as-a-judge," semantic checks, and unit tests) to ensure our features are production-ready and hallucination-resistant.
• Advanced RAG & Reasoning Optimization: Moving beyond "naive RAG." You will implement and tune advanced retrieval strategies (e.g., hybrid search, reranking, agentic retrieval) and optimize complex reasoning loops (e.g., CoT, ReAct) to make our current and future agents smarter and more reliable.
• Production-Grade Model Tuning: Leading the strategy for when, and if, to move beyond simple prompting. You will oversee supervised fine-tuning (SFT) and Parameter-Efficient Fine-Tuning (LoRA) workflows to adapt models to our specific product domains.
• Performance & Cost Engineering: Balancing the "Quality-Cost-Latency" triangle. You will find ways to maintain high-quality outputs while optimizing token usage and reducing inference latency.

Location

The role is based in our tech hub in Madrid, Spain, but we are remote-friendly and open to the CET timezone +/- 2 hours. Way of Working: Remote/Hybrid

What You’ll Need

• Applied MLE Background: You have a proven track record of shipping Machine Learning functionality in a product-focused environment. You prefer "what works in practice" over "what works in theory."
• Bleeding-Edge Awareness: You stay current with the latest AI research and can quickly evaluate new models, techniques, and frameworks for potential product integration.