AI Integration Architect - RDT Data Platforms
AI in this role
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
AI Integration Architect - RDT Data Platforms
As an AI Integration Architect - RDT Data Platforms within the Data Integration, Model Context Protocol (MCP) & Streaming Platforms team, you will serve as a strategic technical leader and hands-on integration expert with core strength in Enterprise Integration Patterns, bridging the gap between enterprise integration infrastructure and modern AI ecosystem advancements (Agentic Workflows, Skills).
In this role, you will establish, refine, and govern robust Integration standards and reference architectures. Your primary focus centres on API-driven paradigms, resilient real-time data streaming, and next-generation frameworks like MCP and A2A. Driven by a high-performing mindset, you will construct end-to-end solutions that safely surface organizational datasets and event pipelines to intelligent systems, fostering scalable, context-aware AI capabilities.
At Roche, we offer a hybrid work model that combines flexibility with in-person collaboration. For now, we require our employees to be in our offices on average two days per week. The specific office days may vary depending on business needs, such as workshops, conferences, town halls, team meetings, and other collaborative events.
The opportunity:
Enterprise Integration & AI Strategy
- Integration & Enterprise Action Layer: Formulate and execute the enterprise architecture strategy for enterprise action layer, enabling governed access to key business capabilities through APIs, events and agent protocols such as MCP, A2A.
- Patterns & Architectures: Redefine integration patterns supporting new protocols, establishing reference architectures and design standards for Skills, Agentic AI, and event-driven AI workflows.
- Governance & Controls: Define, publish, and execute governance standards and controls for AI integrations, establishing Architecture Decision Records (ADRs), API/MCP/Event design reviews, and security frameworks tailored for AI interactions.
Architectural Governance & Platform Engineering
- MCP & API Integration Architecture: Design, standardise, and govern enterprise MCP servers and client architectures, ensuring secure, scalable, and standardized access for AI agents to context, tools, and enterprise data across domains.
- Real-Time Data Streaming & AI Integration Platforms: Architect and deliver low-latency, resilient streaming pipelines leveraging platforms like MuleSoft, Solace, and Apache Kafka on AWS and Kubernetes to power real-time AI capabilities, streaming inference, and contextual memory
Next-Gen AI Protocols & Innovation
- Drive AI & Integration Innovations: Combine deep integration domain skills with emerging AI capabilities to evaluate, pilot, and drive adoption of novel protocols (MCP, A2A), agentic workflows, and AI ecosystem standards.
- Hands-On Prototyping & PoCs: Build high-impact Proofs of Concept (PoCs) validating agentic integration patterns, RAG, and AI skills, directly accelerating implementation and removing technical debt.
- Cross-Functional Collaboration & Mentorship: Partner closely with internal Data & AI streams, product engineering teams, and key stakeholders, serving as an authoritative mentor and advocate for modern integration patterns.
Strategic Collaboration & Technical Leadership
- Internal Collaboration & Stakeholder Management: Collaborate internally across Data & AI streams, partnering with product owners, data engineers, enterprise architects, and business domain leads to align technical capabilities with business strategy.
- Adoption & Advocacy: Promote design-first and protocol-driven thinking, advocating for standardized Integration/AI tools and contextual integration across product lines.
Whoyou are:
- 8+ years of experience as an Integration Architect/SME with deep practical experience integrating Enterprise platforms like ServiceNow, SAP S/4HANA, Workday, Snowflake, and Veeva.
- Enterprise Integration Patterns & Proven Track Record: Core strength and extensive hands-on knowledge in Enterprise Integration Patterns, designing scalable integration solutions combining API management and event-driven architectures (EDA).
- Domain Knowledge: Experience in highly regulated industries (e.g., Pharmaceuticals, Healthcare) is a strong plus.
- AI Ecosystem & Emerging Protocols: Hands-on expertise with next-gen AI protocols (MCP, A2A), agentic workflows and Skills. Knowledge of LLMs, RAG architectures, and vector search is an added advantage.
- Integration & Event Streaming Platforms: Strong technical proficiency in enterprise integration platforms and low-latency streaming infrastructure (MuleSoft, Solace, Apache Kafka/Confluent, AWS Kinesis, REST/gRPC microservices).
- Identity & Secure Agent Security Architecture: Deep experience with OAuth2, OIDC, On-Behalf-Of (OBO) token exchange, and identity propagation to ensure safe, context-aware execution across AI agent and enterprise backend interactions.
- Cloud & Platform Infrastructure: Hands-on experience with AWS, containerization and orchestration (Kubernetes, Docker), and hybrid enterprise deployment patterns.
- Hands-On & High-Performing Mindset: Willingness to get your hands dirty as an integration expert joining a high-performing team, balancing immediate execution needs with long-term architecture goals.
- Stakeholder Management & Communication: Strong track record in handling key stakeholders and simplifying complex AI/integration concepts for both business leaders and engineering teams.
- Mentorship: Proactive approach to guiding engineering teams and promoting collaborative, reusable solutions.
What You Bring to the Roche Data Integration Team
- Deep mastery of Enterprise Integration Patterns paired with extensive hands-on experience connecting core platforms like ServiceNow, SAP S/4HANA, Workday, and Snowflake.
- Practical knowledge in AI protocols (MCP, A2A), agentic AI, LLMs, Skills, RAG architectures, and vector search, backed by hands-on proficiency in MuleSoft, Solace, and Apache Kafka.
- A pragmatic "roll-up-your-sleeves" approach combining technical depth, stakeholder management finesse, and an active drive to define governance controls and redefine patterns for next-generation enterprise integration.
What you get:
- Salary range 19,075 - 26,325 PLN gross based on the employment contract.
- Annual bonus payment based on your performance.
- Dedicated training budget (training, certifications, conferences, diversified career paths etc.).
- Recharge Fridays (2 Fridays off per quarter available).
- Take time Program (up to 3 months of leave to use for any purpose).
- Vacation subsidy available.
- Flex Location (possibility to perform our work from different places in the world for a certain period of time).
- Take Time for Charity (additional paid leave of maximum 2 weeks to engage in the charity action of your choice).
- Private healthcare (LuxMed packages), group life insurance (UNUM) and Multisport.
- Stock share purchase additions.
- Yearly sales of company laptops and cars and many more!
Apply directly and join us in shaping the future of healthcare.
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Want to know what it’s like to be a part of Roche IT first-hand? Check out our blog!
https://careers.roche.com/global/en/we-are-roche
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Compensation & Benefits
The expected salary range for this position, based on the primary location of Warsaw Grafit is 228,900.00 PLN - 425,100.00 PLN. Final compensation will be determined by a number of factors, including your skills, experience, qualifications, and location. In addition to base pay, this role may be eligible for a discretionary annual bonus with a target of 20% subject to both individual and company performance.This position also offers an attractive benefits package.
Learn more about how we reward our employees at Roche.
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.
How we rate this
AI Integration Architect - RDT Data Platforms at Roche rates 74 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.
Works on AI. The daily work is on AI products, without building the model.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.
Prepare for this job
A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.
Skills and AI tools this role asks for
Questions you could be asked
- How would you design a retrieval step so the model answers from real data instead of guessing?
- How do you decide when an AI agent can act on its own versus asking for approval first?
- Describe a typical day in a role like this one: which parts run through AI directly?
- If you removed AI from this role, what would be left, and how do you decide what still needs a human?
Adapt your resume
- List these exact terms on your resume: RAG and AI Agents. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
- Show where AI is part of your daily process, not a one-off project — this role expects it to be a running habit.
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