Ubisoft Senior Software Engineer - AI Applications (W/M/NB) \\\| SmartRecruiters Google Chrome Microsoft Edge Apple Safari Mozilla Firefox . Senior Software Engineer - AI Applications (W/M/NB) Full-time Contract: Permanent Work flexibility: Office-based Company Description Ubisoft is a global leader in gaming with teams across the world creating original and memorable gaming experiences, from Assassins Creed, Rainbow Six to Just Dance and more. We believe diverse perspectives help both players and teams thrive. If youre passionate about innovation and pushing entertainment boundaries, join our journey and help us create the unknown! Job Description Join the Ubisoft AI Initiatives team and architect the future of the information lifecycle at Ubisoft. From advanced hybrid search and RAG pipelines to complex, agentic reasoning, we are engineering the tools that turn raw information into high-velocity decision-making. If you want to push the boundaries of how humans and AI collaborate to solve complex problems, this is your arena. We are seeking a highly experienced Senior Software Engineer to join our team in charge of the development of scalable back-end systems that power these cutting-edge AI applications. Responsibilities As a Senior Software Engineer AI Applications, you will play a critical role in designing and building the core services that enable our solutions. Youll work at the intersection of AI, enterprise cloud-based applications, large-scale data processing, and cloud infrastructure, with significant room for growth and impact. This is why this role requires a deep understanding of modern architectures, AI/ML integration, as well as a passion for solving complex problems. Architect and Develop Back-End Systems: Design and implement scalable, high-performance back-end services to support AI applications. Optimize Performance: Ensure low-latency, high-throughput serving of AI models, agents and APIs, optimizing for both speed and reliability. Collaborate Across Teams: Partner with data scientists and ML engineers to integrate AI models and advanced agents into production systems, ensuring seamless deployment and monitoring. Cloud Infrastructure: Build and maintain cloud-native solutions using platforms like AWS, or Azure, with a focus on scalability, security, and cost-efficiency. Technical Leadership: Mentor junior engineers, conduct code reviews, and contribute to the overall technical strategy of the team. Stay Ahead of the Curve: Keep up-to-date with the latest trends and technologies in AI, cloud computing, and software engineering, and bring innovative ideas to the table. Joining our team as a Senior Software Engineer in AI Applications offers a unique chance to work on industry-leading projects that shape the future of AI technology. You will have the opportunity to: Engage in continuous learning and professional development to stay at the forefront of AI advancements. Take on increased responsibilities and influence the strategic direction of our AI product offerings and drive impactful innovation. Qualifications Relevant experience, skills and knowledge We are seeking a seasoned professional with a strong technical background and a passion for building world-class AI applications. Must-Have Qualifications: Experience: professional and practical software engineering experience, with a focus on back-end development in a compute-intensive and/or data-intensive environment. Programming Skills: Expertise in languages such as Python, Java, Rust, or C++. Cloud Expertise: Hands-on experience with cloud platforms (AWS, GCP, Azure) and containerization technologies (Docker, Kubernetes). AI/ML Integration: Experience deploying and serving machine learning models in production environments. System Design: Strong understanding of system architecture, microservices, and API design. Problem-Solving: Proven ability to tackle complex technical challenges and deliver innovative solutions. Nice-to-Have Qualifications:  Familiarity with Deep Learning architectures, Language Models, Vision Models Understanding of RAG-based architectures (indexing, embedding, vector databases and search, query processing) Experience building and deploying AI agents and multi-agent systems, including agent orchestration frameworks (e.g. LangGraph, Strands Agents, CrewAI), tool integration and agentic workflow design. Experience with serverless architectures and event-driven systems. Contributions to open-source projects or publications in relevant fields. Additional Information Please submit your application documents in English. Ubisoft's perks Profit Sharing, yearly company saving plan. 25 paid time off + 12 additional paid days off. 50% of your transportation pass is paid by the company, lunch vouchers (9/day), healthcare for you and your family, and lots of Ubisoft additional perks. Maternity leaves of 20 weeks, paternity/co-parental leaves of 7 weeks. Our office is located in Saint Mandé, (Metro line 1, Saint Mandé station). Gym available in the building. Recruitment process \\[30 minutes\\]: phone or visio call with a Recruiter, \\[60 minutes\\]: interview with the manager of the role and a Recruiter, \\[60 minutes\\]: interview with members of the AI team \\[60 minutes\\]: during the interview process, you will go through technical assessments with technical experts from Ubisoft. Information about Ubisoft Ubisoft offers the same job opportunities to all, without any distinction of gender, ethnicity, religion, sexual orientation, social status, disability, or age. Ubisoft ensures the development of an inclusive work environment which mirrors the diversity of our gamers community. Check out this guide to help you with your application, and learn about our actions to encourage more diversity and inclusion. 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The role requires professional and practical software engineering experience, with a focus on back-end development in compute-intensive or data-intensive environments. Expertise in programming languages such as Python, Java, Rust, or C++ is necessary. Candidates must have hands-on experience with cloud platforms like AWS, GCP, or Azure, and containerization technologies such as Docker and Kubernetes. Experience deploying and serving machine learning models in production environments is also a requirement. A strong understanding of system architecture, microservices, and API design is essential for this position.