Cloud & AI System Engineer

OVERVIEW At Fadata, we take pride in our ability to adapt quickly to the ever-changing needs of our market and customers. This means that you, too, should be ready to embrace change as circumstances evolve. If you're excited about a fast-paced, dynamic environment where strategy is set but flexibility to grow with the market remains, then hit the apply button.     We have a bold vision: to become the global standard for core software solutions in the insurance industry. Our aim is to achieve this by developing a truly cloud-native solution that can scale limitlessly—and we want you to be part of that journey.     Our values—Trust, Openness, Passion, Innovation, and Care—serve as our guiding compass. They shape how we work every day, our relationships with clients, and the way we collaborate as a team. OPPORTUNITY We are looking for a highly motivated and experienced AI Engineering Lead to join our growing AI Engineering team. You will play a key role in designing, building, and delivering production-ready AI solutions focused on LLM applications, agentic workflows, AI orchestration, RAG systems, and AI automation. This is primarily a hands-on engineering role with technical leadership responsibilities. You will help lead one AI Engineering team through technical execution, mentoring, and engineering best practices, while remaining deeply involved in implementation and solution delivery. You will work closely with Product Managers, Architects and engineering teams to build scalable and reliable AI capabilities that deliver measurable business value in real enterprise environments. YOUR RESPONSIBILITIES * Design, build, and maintain production-ready AI solutions using modern LLM and agentic AI technologies * Develop AI workflows, orchestration layers, RAG pipelines, and AI automation capabilities * Build scalable and maintainable AI services, APIs, and integrations using Python and modern backend engineering practices * Prototype, iterate, and productionize AI capabilities in a fast-moving and experimental environment * Implement prompt engineering, context management, tool usage, and structured AI output strategies * Develop evaluation, validation, testing, monitoring, and feedback mechanisms to ensure AI reliability and quality in production * Contribute to AI governance, observability, security, and operational best practices * Collaborate closely with Architects to align AI solutions with the broader platform architecture and engineering standards * Work closely with Product Managers and stakeholders to translate business needs into practical AI solutions * Provide technical leadership, mentoring, and guidance to our AI Engineering team * Support technical execution alignment, implementation quality, and engineering best practices within the team * Participate in technical interviews, hiring, and the growth of the AI Engineering capability within the organization * Stay current with emerging AI technologies, tooling, and engineering practices relevant to enterprise AI development WHAT YOU BRING TO THE TABLE * Strong software engineering experience with Python and modern backend development practices * Hands-on experience building production-ready AI/LLM applications and workflows * Experience with frameworks such as LangChain, LangGraph, or similar AI orchestration technologies * Experience designing and implementing RAG architectures and vector database integrations * Practical understanding of AI agents, orchestration patterns, tool calling, and context management * Experience working with cloud AI platforms, preferably AWS Bedrock * Strong understanding of AI system reliability, validation, evaluation, monitoring, and governance concepts * Experience building scalable APIs and integrating AI capabilities into enterprise systems * Strong problem-solving skills and ability to work effectively in ambiguous and evolving environments * Excellent communication and collaboration skills with both technical and non-technical stakeholders * Ability to explain complex AI concepts and trade-offs in a clear, practical, and business-oriented way Preferred Qualifications * Experience with AI observability, tracing, and monitoring tools * Experience integrating AI solutions with enterprise platforms and workflows * Understanding of AI security, data privacy, and governance considerations * Experience mentoring engineers or technically leading engineering initiatives * Familiarity with prompt evaluation frameworks, benchmarking, and AI quality validation approaches * Experience working in Agile product development environments What We Value * Pragmatic engineering mindset focused on delivering real business value * Strong ownership and accountability * Curiosity, adaptability, and continuous learning * Collaborative and team-oriented approach * Ability to balance experimentation with production reliability * Attention to quality, scalability, and maintainability * Proactive communication and transparent problem-solving * Passion for building innovative yet practical AI solutions * Ability to thrive in a fast-moving and evolving AI landscape WHY YOU SHOULD JOIN US * Become part of a fast-growing insurance software vendor with multinational teams across Europe – we actually have+15 nationalities in our company * Receive a competitive remuneration package together with great opportunities for personal and professional growth * A positive company culture built around people's wellbeing * No meetings time when we can focus on our main tasks * Work in a dynamic environment with an exceptional team that is always ready to help * A half-day off the second Friday of the month, so you focus on passion projects, boost your creativity or spend time with your loved ones If you are interested in this role, we will be glad to hear from you.

By bringing together next-gen technology and the finest live data available, Genius Sports is enabling a new era of sports for fans worldwide, delivering experiences that are more immersive, interactive and personalized than ever before. Learn more at geniussports.com.  About the Role - AI Engineer, Sports AI  We're looking for an AI Engineer on our Sports AI team to help build the next generation of applied AI systems powering sports analysis, automation, and insights.  These systems use live and historical sports data, including tracking data, structured feeds, broadcast video, commentary, and text, to understand game context, detect & enrich key events, estimate the probability of future events, and generate insights. The outputs from these systems power a range of products and workflows, such as projecting which games or moments will be most exciting to fans and automating parts of manual play-by-play collection using CV/AI. The role spans a broad set of sports modeling and automation problems across multiple sports, including soccer, American football, and basketball.  This role sits at the intersection of machine learning, AI system design, and production engineering. You'll own scoped AI systems end-to-end: framing the relevant modeling problems, constructing the datasets needed to solve them, training and composing models and algorithms, building the inference pipelines that orchestrate them, and rigorously evaluating output quality against messy, real-world data.  You'll work on challenges like aligning signals across multiple sources, handling uncertainty and inconsistency in system outputs, and improving accuracy, latency, and reliability in real-time production workflows. In this role, hands-on ML/AI work will be central: understanding data, developing models and algorithms, evaluating outputs empirically, and iterating in production. You'll also apply LLMs and agentic workflows as part of your broader AI engineering toolkit.    Key Responsibilities   * Own applied AI work end-to-end, from data exploration and early prototypes through evaluation, production integration, and iteration  * Develop and compose models, algorithms, and inference pipelines that convert sports data into structured events, predictions, insights, and confidence-aware outputs  * Build models for problems such as event detection, event likelihood estimation, fan interest & excitement projection, and automation of manual play-by-play collection  * Work with messy, multimodal sports data from tracking systems, video and computer vision outputs, audio, commentary, text, and structured feeds, including imperfect labels and ambiguous real-world examples  * Define and use metrics, evaluation datasets, and benchmarks to measure AI system quality and guide model, algorithm, and product decisions  * Train, adapt, evaluate, and integrate ML models and AI components, including multi-step systems where model, algorithmic, and LLM/agent outputs are composed, validated, and refined  * Design workflows that use human review or correction data to improve evaluation, model iteration, and production output quality where appropriate  * Work closely with CV engineers on training pipelines, labeling workflows, and model deployment patterns  * Partner with product, data platform, infrastructure, and systems engineers to integrate evaluated AI outputs into real-time sports products and automation workflows  * Mentor junior teammates and contribute to team knowledge-sharing, reviews, and experiment design    Qualifications  * 3+ years of experience building production ML, CV, or AI systems  * Ability to translate ambiguous sports product goals into concrete ML tasks, including defining the prediction target, identifying the right data, measuring output quality, and shipping production-ready solutions  * Hands-on production ML/AI experience, including constructing datasets, defining features and labels, training and deploying models, evaluating outputs empirically, and shipping AI system capabilities into production  * Strong modeling judgment across deep learning and classical ML, with experience choosing approaches based on data inputs and problem structure  * Experience with predictive modeling, event detection, data labeling, data quality improvement, and communicating experiment results to technical and non-technical stakeholders  * Ability to evaluate AI system quality beyond anecdotal inspection, including reasoning about ambiguous outputs, imperfect labels, uncertainty, and real-world product tradeoffs  * Strong production engineering fundamentals, including testing, observability, performance, and reliability  * Demonstrated interest in the fast-moving landscape of LLMs, latest models, agentic AI systems, and development frameworks  * Comfortable working in fast-moving, iterative environments with evolving requirements    Preferred Qualifications     * Hands-on experience with LLM-integrated workflows, LLM APIs or cloud AI platforms such as AWS Bedrock, agentic AI systems, multi-agent systems, or evaluation of LLM/agent outputs in production workflows  * Experience with ML/CV domains relevant to sports understanding, such as action recognition, sequence modeling, multimodal modeling, object detection, tracking, or player identification  * Experience working with player tracking data, sports analytics, play-by-play data, labeling platforms, and/or ML training platforms such as Union  * Experience collaborating with CV engineers or integrating CV model outputs into downstream ML workflows  * Experience using human review or correction workflows to evaluate and improve AI system quality  * Experience building production systems in Rust  * Familiarity with streaming, event-driven, audio/video, or real-time data workflows is a plus  * Background or strong interest in sports, especially soccer, American football, and basketball  The salary for this role is based on an annualized range of $160,000 - $190,000 USD. This role will also be eligible to take part in Genius Sports Group's benefits plan. We enjoy an ‘office-first’ culture and maximize opportunities to collaborate, connect and learn together. Our hybrid working models differ depending on your role and location. Occasional travel may be required. As well as a competitive salary and range of benefits, we’re committed to supporting employee wellbeing and helping you grow your skills, experience and career. Learn more about how rewarding life at Genius can be at Reward | Genius Sports. One team, being brave, driving change  We strive to create an inclusive working environment, where everyone feels a sense of belonging and the ability to make a difference. Learn more about our values and culture at Culture | Genius Sports. Let us know when you apply if you need any assistance during the recruiting process due to a disability.