Full-Stack Software Engineer (Frontend, Backend & Cloud) – Applied & Agentic AI Systems
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
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., ~9 members) powered by advanced coding agents (like Claude Code) to develop and ship solutions faster than ever before (through 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 AI / 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.
Skills
Must-have:
Software Engineering Best Practices: Robust automated testing (TDD) to verify both code written by AI agents and dynamic UI components generated at runtime.
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.
APIs and integrations: Building API-driven applications and integrating different enterprise systems into one solution.
Should-have:
Data & AI Tooling: Experience integrating with modern databases (Snowflake, OpenSearch). Familiarity with the Model Context Protocol (MCP), graph databases, and Generative UI libraries.
aSDLC: leveraging Agentic AI in the Software Development Lifecycle
Building scalable, secure, resilient, and highly available systems.
Could-have:
Regulatory Compliance: Proven experience in working within highly regulated industries.
Additional Qualifications
Security Mindset: Strong understanding of enterprise security risks, IAM, and safe data handling along with a strong understanding of responsible AI deployment.
Communication: Be an excellent problem solver, detail-oriented, and a great communicator, able to present complex technical matters clearly to diverse audiences. Be able to communicate in English at the level of C1+.
Be deeply interested in developments in AI, staying up-to-date with the latest developments in agentic SDLC, cloud computing, and software development practices.
Be able to communicate in English at the level of: C1+.
Working Hours: Located in Hyderabad, India, with working hours structured to capture the 'golden hours' of overlap with Central European Time (typically running through the IST evening).
#Hyd2026
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
Full-Stack Software Engineer (Frontend, Backend & Cloud) – Applied & Agentic AI Systems at Roche scores 89 out of 100 on AI centrality, which makes it AI Level 4 of 4 (Builds AI) on this board. The level measures how much of the work is AI, not seniority.
AI Level 4. Building AI systems is the job itself: without AI, the role would not exist.
- AI Level 480 to 100
- AI Level 360 to 79
- AI Level 240 to 59
- 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
Questions you could be asked
- How do you decide when an AI agent can act on its own versus asking for approval first?
- How do you think about the risk of an AI system in this kind of role failing silently?
- What are the limits of Claude that you've run into, and how did you work around them?
- What's a project where you used Claude Code hands-on?
- How would you decide a model or AI system is ready to ship?
Adapt your resume
- List these exact terms on your resume: AI Agents, AI Safety, Claude, and Claude Code. 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.
- Lead with what you built, trained or shipped — this role is judged on the AI system itself, not the tools around it.
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