Sr. Specialist Software Engineer

Portugal - Lisbonsenior

Software EngineerSoftware Engineering

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Quick Summary

Key Responsibilities

Design, develop, and maintain scalable full-stack web applications using React.js, Next.js, Node.js, Typescript Build responsive, mobile-first,

Requirements Summary

Doctorate Degree OR Master’s degree with 4 - 6 years of experience in Computer Science, IT or related field OR Bachelor’s degree with 6 - 8 years of experience in Computer Science,

Technical Tools

Software EngineerSoftware Engineering

Information Systems

Join our team at AMGEN Capability Center Portugal, consistently recognized among the top companies in the Best Workplaces™ ranking by Great Place to Work® in Portugal. In 2026, we were once again distinguished as one of the top Best Workplaces in the country (category 201–500 employees), reinforcing our commitment to an exceptional employee experience and workplace culture.

We are a team of over 500 talented individuals, spanning more than 30 functions and areas of expertise, and representing over 40 nationalities. Together, we bring diverse perspectives and professional backgrounds to help shape the future of healthcare through innovation and technology.

This is your opportunity to explore a world of possibilities across areas such as Data & Analytics, Digital, Technology & Innovation, Cybersecurity, R&D Operations, Global Distribution, Finance, Regulatory Affairs, General & Administrative, Human Resources, and many more.

Located in the heart of Lisbon, our AMGEN office fosters a culture of innovation, excellence, and purpose. Come thrive with us at AMGEN, supporting our mission To Serve Patients.

What we do at AMGEN matters in people’s lives.

Sr. Specialist Software Engineer

Amgen is seeking a Specialist Software Engineer - Full Stack to design, develop, and support modern AI-enabled web applications that power Insights and Field Intelligence capabilities.

This role focuses on building scalable, responsive, and intelligent full-stack applications using React, Next.js, Node.js, and cloud-native technologies while integrating AI/ML capabilities such as Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI agents, and intelligent workflow automation.

The ideal candidate combines strong front-end and back-end engineering expertise with hands-on experience integrating AI services and APIs into enterprise applications. The successful candidate should have a passion for modern application development, AI innovation, and building intelligent systems that improve business productivity and decision-making.

Responsibilities

~2 min read

→Design, develop, and maintain scalable full-stack web applications using React.js, Next.js, Node.js, Typescript
→Build responsive, mobile-first, and user-centric interfaces that support enterprise Insights and Field Intelligence use cases.
→Develop reusable UI components, application frameworks, and shared libraries following modern front-end engineering best practices.
→Design and develop secure and scalable backend services, APIs, and microservices using Node.js and REST/GraphQL architectures.
→Implement server-side rendering (SSR), static site generation (SSG), and modern web optimization techniques using Next.js.
→Ensure application scalability, performance optimization, accessibility, and cross-browser compatibility.
→Design and develop AI-enabled applications leveraging Large Language Models (LLMs) such as OpenAI models and enterprise AI services.
→Develop Retrieval-Augmented Generation (RAG) solutions using vector databases and enterprise knowledge sources.
→Design and implement AI agent workflows and orchestration frameworks to automate business processes and insight generation.
→Integrate AI capabilities into enterprise web applications, APIs, and workflows for real-time intelligence and automation.
→Implement context management approaches such as Model Context Protocol (MCP) or similar AI orchestration frameworks.
→Evaluate and adopt emerging AI technologies, frameworks, and engineering best practices.
→Design, build, and maintain scalable APIs and backend integration services supporting enterprise and AI-driven applications.
→Develop integrations with enterprise platforms including CRM, analytics, and business intelligence systems.
→Build secure and reusable API services enabling AI-driven workflows and data access patterns.
→Implement monitoring, logging, observability, and error handling across APIs and application services.
→Leverage AWS cloud services to build scalable, resilient, and secure application platforms.
→Implement CI/CD pipelines and DevOps best practices for application deployment and lifecycle management.
→Support containerized application deployment using Docker and cloud-native deployment approaches.
→Optimize application performance, scalability, and operational reliability in cloud environments.
→Participate in agile ceremonies including sprint planning, backlog refinement, estimation, and retrospectives.

→Create and maintain technical documentation including architecture diagrams, API specifications, deployment procedures, and operational guides.

Requirements

~1 min read

Doctorate Degree OR
Master’s degree with 4 - 6 years of experience in Computer Science, IT or related field OR
Bachelor’s degree with 6 - 8 years of experience in Computer Science, IT or related field OR Diploma with 10 - 12 years of experience in Computer Science, IT or related field

Strong hands-on experience developing full-stack applications using React.js, Next.js, Node.js, Typescript, Javascript
Strong experience building scalable RESTful APIs and backend services
Hands-on experience building Retrieval-Augmented Generation (RAG) pipelines and integrating vector databases.
Understanding of AI agent architectures, orchestration frameworks, and context-aware AI systems.
Experience integrating AI capabilities into web applications, APIs, and enterprise workflows.
Experience with AWS cloud data platforms

Experience with machine learning workflows (Databricks ML, or similar)
Familiarity with Model Context Protocol (MCP) or similar AI context management approaches.
Knowledge of real-time/streaming architectures
Understanding of field analytics, CRM data models, or commercial insights use cases