Internal Systems Agentic AI Engineer at Roche

Sant Cugat del Vallès, Catalonia, Spain -

Full Time

Start Date

Immediate

Expiry Date

23 Aug, 26

Salary

0.0

Posted On

25 May, 26

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Agentic AI, Data Engineering, Software Engineering, Multi-agent Workflows, API Integration, Retrieval Systems, Asynchronous Programming, Business Process Analysis, Data Modernization, LLMs, Cloud Architecture, Requirements Engineering, Systems Engineering, Observability, Python, English Proficiency

Industry

Biotechnology Research

Description

At Roche you can show up as yourself, embraced for the unique qualities you bring. Our culture encourages personal expression, open dialogue, and genuine connections, where you are valued, accepted and respected for who you are, allowing you to thrive both personally and professionally. This is how we aim to prevent, stop and cure diseases and ensure everyone has access to healthcare today and for generations to come. Join Roche, where every voice matters. The Position Who we are The Digital Innovation and Operational Services Chapter is a global team in R&D that focuses on internal improvement: increasing productivity, efficiency, and the ability of the R&D organization to collaborate across its global organizational interfaces. Our work involves reducing the complexity of our systems, harmonizing processes, tools, and business practices, and building connections across geographical and organizational silos. The Opportunity To support our digitalization journey, we are looking for a talented and driven Internal Systems Agentic AI Engineer with a passion for eliminating wasteful and mundane tasks through innovative technology. In this role, you will be instrumental in enabling our organization’s transformational transition to Agentic AI by building agentic solutions for our internal processes.. You will bridge the gap between technical data engineering and business process analysis, ensuring our internal R&D and enterprise systems operate in a seamless, automated, and data-driven ecosystem. As part of a global team, you will collaborate with experts coming from IT, business processes, and R&D science backgrounds to build solutions that enhance the productivity of our internal tool service and support teams, while maintaining the highest standards of data integrity, privacy, and security. Key Responsibilities Agentic AI Solutions: Combine your technical knowledge in Agentic AI, our internal systems and data architectures, and work with business process experts and IT colleagues to enable agentic solutions to support the scalability of our internal systems and support services. Data Modernization: Support our digitalisation strategy by driving the standardization and migration of data from legacy systems to AI-ready modern architectures for scalability and performance. Business Process Analysis and Requirements Engineering: Act as a bridge between technical teams and business units to analyze, map, and define requirements for specific use cases in support of digitalisation initiatives and the evolution of DSI-owned tools. Collect input from R&D scientists and engineers to support your assessments. Global Collaboration: Participate in global teams across our R&D organization in support of digitalisation initiatives, working with scientists, engineers, and IT professionals in Spain, the US, Germany, and Switzerland to bring value to our organization on a global scale. Operate with limited guidance Develop and maintain an awareness of the Roche organization and key organizational drivers as well as the relevant processes, customers, and products. Work within existing procedures to perform a range of assignments related to own projects / scope. Solves complex problems by analyzing possible solutions using experience, judgment, and precedents. Fulfill responsibilities with a limited to moderate level of guidance and direction. Who You Are You are a proactive problem-solver who thrives in a multicultural environment. You are not just a coder; you are a "thinker" who understands the business impact of data and automation. You are comfortable navigating ambiguity and are committed to continuous learning in the rapidly evolving landscape of AI and automation, supporting our colleagues to speed up their engineering and science. Basic Qualifications Education: Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Engineering, Software Engineering, or a related technical field. Experience: 3-5+ years of professional experience in software engineering, computer science,, automation, or a similar technical role. Technical Skills: Orchestration & Logic: Designing stateful, multi-agent workflows using cyclic reasoning patterns and self-correction loops. Tool Use & Connectivity: Architecting secure interfaces for agents to execute external functions and interact with third-party APIs. Context & Memory: Implementing long-term memory architectures and advanced retrieval systems for persistent context. Observability & Evaluation: Building automated pipelines to trace agentic "thought processes" and measure output reliability. Systems Engineering: Developing production-grade, asynchronous code to handle non-deterministic agent behaviors and error recovery. Language: Excellent command of English (written and spoken) for effective collaboration in a global environment. German language skills are a plus. Global Flexibility: Ability to support a flexible schedule that periodically accommodates collaboration across multiple time zones (primarily CET and PST), ensuring effective communication with global stakeholders and project teams Travel: Occasional travel, up to 1 week, 1-2 times per year to other Roche sites in US and Europe Desired Skillsets & Experience Data Modernization: Experience with migration of data from legacy systems to modern architectures to ensure scalability and performance. Industry Knowledge: Experience working in the Diagnostics industry or other highly regulated environments (e.g., Pharma, MedTech). Regulatory Context Exposure: Exposure to Design Control, formal system engineering / product development processes Enterprise Platforms: Familiarity with SAP S/4HANA environments, HR/Learning systems like Workday or Cornerstone, specifically regarding data extraction and workflow automation. R&D Tools: Familiarity with electronic Lab Notebook, LIMS systems, equipment / asset management systems. AI & Automation: Hands-on experience with LLMs, Agentic AI frameworks, or building conversational AI interfaces (Chatbots). Cloud Architecture: Knowledge of cloud-based data warehouses (e.g., Snowflake) and cloud providers (AWS, Azure, or GCP). Communication: Ability to translate complex technical findings into actionable business insights for non-technical stakeholders. Who we are A healthier future drives us to innovate. Together, more than 100’000 employees across the globe are dedicated to advance science, ensuring everyone has access to healthcare today and for generations to come. Our efforts result in more than 26 million people treated with our medicines and over 30 billion tests conducted using our Diagnostics products. We empower each other to explore new possibilities, foster creativity, and keep our ambitions high, so we can deliver life-changing healthcare solutions that make a global impact. Let’s build a healthier future, together. Roche is an Equal Opportunity Employer. We believe it’s urgent to deliver medical solutions right now – even as we develop innovations for the future. We are passionate about transforming patients’ lives. We are courageous in both decision and action. And we believe that good business means a better world. That is why we come to work each day. We commit ourselves to scientific rigor, unassailable ethics, and access to medical innovations for all. We do this today to build a better tomorrow. We are proud of who we are, what we do, and how we do it. We are many, working as one across functions, across companies, and across the world. We are Roche.

Responsibilities

Develop and implement Agentic AI solutions to automate internal R&D processes and increase organizational productivity. Bridge the gap between technical data engineering and business process analysis to modernize legacy data architectures.