Level

Roche

Solution Architect

AI in this role

langchainlanggraph
ragai-agents

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 Agentic Solution Architect As a key driver of technological innovation, you will leverage cutting-edge AI technologies and advanced architectures to deliver strategic business value for Roche China. You will lead the end-to-end design, development, iterative enhancement, and ecosystem integration of the AI infrastructure and platform, ensuring all systems strictly adhere to enterprise security and compliance standards. We are seeking a visionary architect who combines enterprise-level system design, platform engineering methodologies, and agile delivery with profound AI expertise.

In this role, you will be responsible for:


AI Agent Development & Management Platform

  • Agent Identity& Runtime: Architect and manage robust systems for agent Identity and registration, alongside building highly scalable agent runtimes and internal/external agent marketplaces.
  • Agent Gateway & Guardrails: Design dedicated agent gateways to manage routing, establishing strict agent guardrails to ensure autonomous operations remain within safe, compliant boundaries.
  • Agent Observability & Optimization: Implement comprehensive agent observability, evaluation frameworks, and optimization loops to trace agent reasoning and performance.
  • Tool & Ecosystem Integration: Drive the seamless integration of tools, APIs, and Model Context Protocol (MCP) systems to empower agent capabilities.
  • Advanced Database Integration: Design and implement platform context retrieval capabilities with a heavy focus on Vector Databases (VectorDB) and Graph Databases (GraphDB) to enable complex RAG architectures. Enable the agentic applications across advanced platform tools and diverse data ecosystems, 
  • Agentic Governance Frameworks: Architect, design, and develop highly scalable AI and Agentic applications, leveraging mainstream frameworks such as LangChain and LangGraph.

Architecture Capability & Engineering Excellence

  • Microservices Architecture & DDD: Drive Domain-Driven Design (DDD) to decompose APIs based on complex business requirements, defining clear service boundaries, contracts, and data models.
  • Backend System Design: Design and optimize backend systems utilizing diverse API standards (REST, gRPC, GraphQL), database technologies (SQL, NoSQL), messaging systems (Kafka, RabbitMQ), and caching mechanisms.
  • Architectural Strategy: Evaluate and implement appropriate architectural patterns (such as Event-Driven, CQRS, DDD, and Serverless) by conducting thorough trade-off analyses.
  • Engineering Excellence: Establish and enforce rigorous coding standards, comprehensive unit/integration testing protocols, robust code review processes, and maintain a track record of high-quality product delivery.
  • Driving NFR design/implementation : Lead the architectural definition and enforcement of Non-Functional Requirements (NFRs) across the AI platform. You will ensure systems are compliant with internal GxP and security frameworks (SRA/SER/VRA/PIA) while driving "Shift-Left" testing for performance and security. You will define measurable SLOs for agent performance, oversee the design of robust security guardrails (e.g., prompt injection defense, RBAC for RAG), and implement comprehensive observability and FinOps strategies to balance enterprise-grade reliability with operational efficiency. 

Platform Engineering, Cloud Computing & DevOps

  • Kubernetes & Cloud-Native Engineering: Lead the deployment, administration, and full lifecycle management of Kubernetes clusters. Drive platform hardening and component reusability leveraging mainstream CNCF projects (Prometheus, Grafana, OpenTelemetry, ELK).
  • Hands-on Cloud DevOps & IaC: Drive Infrastructure as Code (IaC) automation utilizing Terraform, CloudFormation, and CLI tools. Manage enterprise-level private and public cloud environments, ensuring robust IAM, network planning, and data encryption.
  • Observability & FinOps: Design and integrate comprehensive observability solutions (Metrics, Logs, Tracing) and alerting systems to ensure transparent monitoring of application performance, usage, and FinOps costs.

Demand Management & Collaboration

  • Project & Delivery Management: Drive large-scale, role-based project execution applying standard Project Management Methodologies (PMM), ensuring alignment with pharmaceutical industry compliance standards.
  • Agile Leadership & Delivery: Champion Agile and Scrum methodologies, coordinate cross-team delivery through CI/CD pipelines (GitLab/GitHub, JFrog Artifactory), and manage project backlogs.
  • Cross-Functional Team Leadership: Facilitate highly efficient collaboration across global and local cross-functional teams, ensuring seamless communication in both fluent Chinese and English. Provide architectural guidance and foster team capability growth.
  • Documentation: Author critical architectural documents and govern comprehensive technical documentation across platforms like GitLab MD and Confluence.

Qualifications

  • Experience: 10+ years of experience as a Solution Architect, with a minimum of 2+ years of hands-on experience specifically in AI Architecture or AI Platform design. Experience in the pharmaceutical, life sciences, or top-tier tech industries is highly preferred.
  • Agentic AI Mastery: Hands-on experience developing Agentic applications using frameworks such as LangChain and LangGraph, alongside deep architectural knowledge of agent platforms, runtime environments, and guardrails.
  • Data Integration: Familiarity with Vector Databases (VectorDB) and Graph Databases (GraphDB), alongside high proficiency in RAG architecture design.
  • Cloud & Platform Engineering Mindset: In-depth understanding of Cloud-Native architectures (e.g., AWS, Alibaba Cloud) and extensive hands-on experience using Terraform, Ansible, Packer, and CloudFormation for automated deployment.
  • Hands-on Coding & DevOps: Mastery of at least one core backend development language (e.g., Python, Go). Expertise in building robust, end-to-end CI/CD pipelines utilizing tools such as GitLab and JFrog.
  • Infrastructure & Security: Deep mastery of the Kubernetes ecosystem and full-lifecycle cluster management. Rich experience in High Availability (HA) system design, Disaster Recovery, RBAC, and integrating enterprise-level components (SSO, LDAP, Bastion hosts).
  • Language: Fluent bilingual capabilities in both English and Mandarin, enabling seamless architectural discussions globally and locally

 

 

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 score this

Solution Architect at Roche scores 64 out of 100 on AI centrality, which makes it AI Level 3 of 4 (Works on AI) on this board. The level measures how much of the work is AI, not seniority.

Classification

AI Level 3. The daily work is on or around AI systems, without necessarily building the model: remove AI and the job is hollow.

  1. AI Level 480 to 100
  2. AI Level 360 to 79
  3. AI Level 240 to 59
  4. AI Level 10 to 39

Bands 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

RagAI AgentsLangChainLangGraph

Questions you could be asked

  1. How would you design a retrieval step so the model answers from real data instead of guessing?
  2. How do you decide when an AI agent can act on its own versus asking for approval first?
  3. What are the limits of LangChain that you've run into, and how did you work around them?
  4. What's a project where you used LangGraph hands-on?
  5. Describe a typical day in a role like this one: which parts run through AI directly?

Adapt your resume

  • List these exact terms on your resume: Rag, AI Agents, LangChain, and LangGraph. 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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