Staff AI Engineer at bsport

Barcelona, Catalonia, Spain -

Full Time

Start Date

Immediate

Expiry Date

01 Jul, 26

Salary

0.0

Posted On

02 Apr, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Python, Machine Learning, LLMs, Agentic AI, LangChain, PydanticAI, RAG pipelines, MLOps, Model registry, Drift detection, Cloud-native, AWS, Kubernetes, Databricks, Apache Airflow, CI/CD

Industry

Wellness and Fitness Services

Description

We are bsport. The place to be! bsport is an all-in-one platform combining boutique fitness and advanced technology. Our platform helps our partners manage their bookings, payroll, marketing and more, to streamline operations and boost their commercial success. Since we launched in 2019, we have already achieved the following: We’ve built a community of over 10 million users 🤝 In December 2024 we have finalised the biggest Series B (€30 million)🏆 Grown our team to more than 200 employees 🚀 We’re continuing to grow to become the #1 tech partner for boutique studios in Europe and the rest of the world! Join us to write the next chapter of your career! 🎯 What you'll own & the role The Data team at bsport is building the AI platform that will power the next generation of intelligent features across our product. This platform sits at the core of how we detect opportunities, automate workflows for our partners, and run the agentic systems that make bsport the strategic partner for studios in their operation and growth. As a Staff AI Engineer, you will own the architecture and engineering of this platform: from the infrastructure that serves models in production to the pipelines that evaluate, monitor, and continuously improve them. You will work closely with Product, Engineering, and the broader Data team to define how AI capabilities are built, deployed, and maintained at bsport. As a Staff AI Engineer at bsport, you will: Set the technical direction for AI/ML infrastructure: defining standards, reviewing architectures, and driving decisions on tooling and frameworks. Build and own the production infrastructure that takes ML and LLM-powered solutions from prototype to live product, ensuring reliability, scalability, and fast iteration cycles. Lead the development of agentic AI systems for domain-specific business problems, including systems of agents, fine-tuning, RAG pipelines, and full lifecycle ownership. Define model evaluation strategies, performance monitoring, and key indicators to measure the real-world impact of deployed solutions. Ensure AI systems are safe, observable, and maintainable by including guardrails, drift detection, and responsible deployment practices. Collaborate with Product and Engineering to translate complex business problems into well-scoped AI projects, and communicate results clearly to non-technical stakeholders. Mentor and support other engineers on the Data team on productionization of ML and AI. 🌟You would be great fit if you have: 7+ years of experience as a Machine Learning Engineer or Applied AI Engineer, with a meaningful portion in production environments. Strong Python skills and experience building robust, production-grade ML systems. Hands-on experience with LLMs and agentic AI frameworks (e.g. LangChain, PydanticAI, or similar), including RAG pipelines and tool-calling agents (fine-tuning experience a plus) Experience with MLOps practices: model registry, monitoring, and drift detection. Proven ability to take ML solutions from prototype to production, including evaluation frameworks, versioning, and iteration. Comfortable working in a cloud-native environment and collaborating with SRE on deployment and infrastructure concerns. Ability to drive architectural decisions and define ML best practices across a team. Strong communication skills: comfortable translating technical findings into business impact for diverse stakeholders. Experience with multi-tenant ML model deployment in a SaaS environment a plus. 🧰 Stack Languages: Python LLM & Agentic: LangFuse, PydanticAI Data Platform: Databricks, Apache Airflow Cloud & infra: AWS, Kubernetes CI/CD: GitLab CI, ArgoCD Observability: Grafana, Sentry 💬 Our Hiring Process: 👋🏼 Interview with Talent 🎙️ Tech Talk 🧑🏽‍💻 Live Coding 📐 System Design 🤝 Final Interview with Founder: cultural fit 🌈🌍 Diversity is one of our most valuable assets, and we are committed to fostering an inclusive environment where everyone can contribute their best work. We welcome applicants from all backgrounds, identities, and experiences to help us build a more inclusive, equitable team. If you’re excited about this role but don’t meet every qualification, we encourage you to apply-curiosity, adaptability, and a willingness to learn are just as important to us as specific skills. What We Offer We believe great work comes from happy, supported people-that’s why we offer meaningful perks designed to promote balance, growth, and connection. 💵 Attractive compensation package Competitive salary packages based on your experience and role. 💻 Work-Life harmony Hybrid model with remote days to support balance and flexibility. 🌎 Work from anywhere Enjoy up to 15 days of remote work from abroad each year. 💪🏽 Exclusive perks helloCSE: discount platform for fitness, shopping, culture, cinema, live events 🌍 Diverse fun loving team Multicultural colleagues, after-work events, team-building & more.

Responsibilities

You will own the architecture and engineering of the AI platform, including infrastructure for model serving and production pipelines. You will lead the development of agentic AI systems and define strategies for model evaluation, monitoring, and performance measurement.