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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 Job description We are looking for a highly skilled, deeply hands-on Full-Stack Software Engineer who will cover frontend UI, backend architecture, cloud deployment, and DevOps engineering all under one hat. Since our team already includes dedicated AI Engineers and Data Engineers, your primary mission is to be the foundational software engineering anchor: building the robust, scalable, and secure user interfaces, infrastructure, integrations, and server-side logic that allows our AI solutions to thrive in a production environment. Description of the area At Roche Digital Technology, we are advancing the boundaries of Applied AI. As part of our strategic initiatives, we are enabling high-value AI solutions spanning advanced agentic frameworks, Generative AI applications, and classical Machine Learning. The Applied AI Engineering Team is tasked with building these innovative AI applications end-to-end to solve complex business challenges in healthcare. In the 2026 tech landscape, the lines between traditional disciplines have blurred. We operate in small agile teams (e.g., ~6 members) powered by advanced coding agents (like Claude Code) to develop and ship solutions faster than ever before (Agentic SDLC). Job Responsibilities Frontend Architecture & Generative UI: Develop highly scalable, reusable UI components using expert-level TypeScript and modern frameworks (React/Next.js or Angular 16+). Shift from static layouts to flexible, dynamic interfaces that gracefully handle unpredictable data and real-time LLM streams. Core Backend Engineering & API Design: Design and build highly scalable, reusable backend services and APIs (using Python) that serve as the backbone for multi-agent workflows and GenAI applications. Build, host, and secure Model Context Protocol (MCP) servers and standard APIs to standardize data exchange. Cloud Architecture & DevOps Excellence: Design, implement, and manage secure and scalable cloud infrastructure (primarily AWS) tailored for diverse AI workloads. Apply Infrastructure-as-Code (IaC) practices using Terraform. Build, maintain, and optimize fully automated CI/CD pipelines and manage application containerization (Docker). Agentic SDLC & Engineering Excellence: Leverage AI coding assistants and autonomous agents (e.g., Claude Code, Ona) daily to accelerate full-stack development cycles. Conduct rigorous code reviews for both human-written and AI-generated code. Qualifications / Education / Experience Experience: 7+ years of strong software engineering experience with a demonstrable focus on backend development, cloud infrastructure, advanced frontend architecture, and DevOps. AI Integration Experience: Proven experience building backends for complex solutions and LLM-powered applications, managing streaming responses, and translating non-deterministic AI outputs into safe, functional user interfaces. Agentic Workflow: Proven experience leveraging AI coding agents within an agentic SDLC to accelerate feature delivery. Hold a B.Sc., B.Eng., M.Sc., M.Eng., PhD, or equivalent in Computer Science, Software Engineering, or a related field. Be a passionate builder, staying continuously up-to-date with the latest developments in cloud computing, backend architectures, frontend paradigms, and AI integrations. Be team-oriented, proactive, and collaborative, thriving in a fast-paced environment where roles are fluid and multidisciplinary. Have a deep sense of accountability, capable of diagnosing complex system-level issues across the entire stack, and able to step into a Tech Lead role when necessary. Technical Skills Frontend & User Interface: Deep expertise in TypeScript and a major framework (React/Next.js or Angular 16+). Strong capability in complex state management and handling real-time data flow. Backend Programming: Advanced, production-grade proficiency in Python. Excellent enterprise API design and microservices architecture skills. Cloud & DevOps: Deep expertise in AWS (IAM, Lambda, S3, ECS, etc.), Docker, CI/CD tools (e.g. GitHub Actions), and Terraform. Data & AI Tooling: Experience integrating with modern databases (Snowflake, OpenSearch). Familiarity with the Model Context Protocol (MCP), graph databases and Generative UI libraries. Software Engineering Best Practices: Robust automated testing (TDD) to verify both code written by AI agents and dynamic UI components generated at runtime. Additional Qualifications Security Mindset: Strong understanding of enterprise security risks, IAM, and safe data handling .
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.