默克药厂
Principal Full-Stack Software Engineer
Principal Full-Stack Software Engineer
发布于 3 小时前普通员工/个人贡献者
AI 估算 · 6–10万 · AI 参考估算
Jerusalem, Jerusalem, Israel
高级经验
本科
全职员工仅现场办公全栈开发
全栈开发
Agentic Workflows
Ai Integration
Apis
CI/CD
Cloud-Native
Containerization
Full-Stack Development
Llm
值不值得投
86综合评分
综合评分 86
A highly impactful, technically advanced Principal Full-Stack role in a global pharma R&D team, offering strong purpose and competitive compensation with flexible culture.
从薪资福利、成长发展、工作生活和使命价值四个维度综合评估，方便横向比较。
薪资怎么样
8万
比全栈开发中位数高
发布情况
新岗位 · 今天发布
公司情况
这家公司招聘很活跃
60 个在招
市场机会
选择面较广
全栈开发 · 约 290 个在招
职位详情
关于这个职位
As a Principal Full-Stack Software Engineer, you will design, prototype, and build advanced AI applications for pharmaceutical R&D. You will translate scientific needs into robust, scalable software, integrating LLMs and agentic workflows to accelerate drug discovery and development.
最低要求
Bachelor’s or master’s degree in computer science, software engineering, information technology, or a related technical discipline.
Minimum of 5 years of relevant experience in full-stack or backend software engineering, including rapid prototypes and production-grade applications.
Proven ability to translate ambiguous user needs into functioning software prototypes and evolve them into robust solutions.
Strong expertise in backend application development, APIs, databases, service-oriented architectures, and enterprise integration patterns.
Hands-on experience with modern frontend technologies to independently develop complete user-facing applications.
Strong programming experience in Python and practical experience with modern frontend or backend technology stacks.
Experience integrating applications with multiple data sources, external services, analytical models, AI systems, or enterprise applications.
Comfortable building lightweight prototypes rapidly while making appropriate architectural decisions.
Practical experience with relational and non-relational databases, data modelling, workflow state, caching, asynchronous processing, and event-driven patterns.
Experienced with modern software engineering practices: automated testing, code review, version control, CI/CD, containerization, observability, and cloud-based deployment.
Understanding of application security principles: authentication, authorization, secure API design, secrets management, data protection, and auditability.
Experience designing resilient applications with error handling, retry mechanisms, fallback behaviours, and monitoring.
Comfortable integrating probabilistic and non-deterministic AI components into reliable software applications.
Collaborate effectively with AI engineers, ML scientists, UX specialists, business stakeholders, and enterprise IT teams.
Strong analytical, communication, and problem-solving skills to translate complex requirements into clear technical implementations.
工作职责
Design, prototype, build, and evolve software applications that enable advanced AI solutions within the Advanced Data Science team.
Rapidly translate scientific and business needs into functioning prototypes and develop them into robust, maintainable, and scalable applications for pharmaceutical R&D.
Work closely with scientists, business stakeholders, Applied AI Engineers, ML experts, Frontend/UX Engineers, and Lead Applied AI Engineer across the complete application stack.
Develop proof-of-concept applications for new AI-enabled workflows, designing them with a clear path toward validation, deployment, and sustainable use.
Build backend services, APIs, user-facing components, data-access layers, workflow logic, state-management mechanisms, and integrations with scientific tools and enterprise services.
Connect large language models, agentic workflows, analytical models, and enterprise data sources into coherent applications.
Take end-to-end engineering ownership of solutions across their lifecycle, moving between rapid prototyping and production-grade development.
Strengthen architecture, testing, security, performance, observability, error handling, auditability, and maintainability as use cases mature.
Ensure applications remain reliable even when AI models, tools, or external services behave unpredictably.
Establish and apply strong software engineering practices, including modular design, version control, automated testing, code review, CI/CD, containerization, logging, monitoring, and technical documentation.
Promote the reuse of software components and application patterns across use cases without slowing down early experimentation.
Work in close partnership with IT architecture, infrastructure, cybersecurity, and platform teams to complement IT ownership of shared platforms and enterprise infrastructure.
Stay current with modern full-stack development, cloud-native architectures, and AI application engineering to demonstrate value quickly while ensuring secure, scalable enterprise applications.
优先资格
Experience in pharmaceutical R&D, healthcare, life sciences, or another regulated environment is considered an advantage.
AI 洞察
优缺点分析
优点
- Work on cutting-edge AI and LLM applications in the highly impactful healthcare and pharmaceutical R&D sector.
- Join a diverse, inclusive, and flexible global team with opportunities for personal development and career advancement.
- Balancing the need for rapid prototyping with the strict requirements of production-grade, secure, and compliant software in a regulated pharmaceutical environment.
- Integrating non-deterministic AI components into reliable enterprise applications requires strong architectural and problem-solving skills.
- Experienced full-stack engineers passionate about applying AI and modern software engineering to solve complex scientific and healthcare challenges.
缺点 / 挑战
暂无明显挑战项
角色解读
- Progress from rapid prototyping to owning end-to-end engineering of enterprise AI applications.
- Opportunity to lead technical initiatives within the Advanced Data Science team and shape the architecture of AI-driven workflows in healthcare.
- Design, prototype, and build full-stack software applications for advanced AI solutions in pharmaceutical R&D.
- Translate scientific needs into functioning prototypes and evolve them into scalable, maintainable applications.
- Collaborate with data scientists and AI engineers to integrate LLMs and agentic workflows into enterprise applications.
- Strong expertise in Python and modern frontend/backend stacks, with hands-on experience in APIs, databases, and cloud-native architectures.
- Proven ability to build rapid prototypes and production-grade software, integrating AI/ML models and enterprise data sources.
- Solid understanding of software engineering practices like CI/CD, containerization, and application security.
申请策略
- Tailor your portfolio to demonstrate how you translate ambiguous scientific or business needs into functional software.
- Be prepared to discuss how you ensure reliability when integrating probabilistic AI components.
- Highlight your experience in building both rapid prototypes and production-grade full-stack applications, especially with Python and modern frontend frameworks.
- Showcase projects where you integrated AI/ML models, LLMs, or complex data sources into user-facing applications.
- Emphasize your expertise in cloud-native architectures, CI/CD, and application security.
- Deepen your knowledge of agentic workflows, LLM integration, and resilient application design (error handling, retry mechanisms).
- Familiarize yourself with pharmaceutical R&D workflows or regulated environment compliance if you lack prior healthcare experience.
面试指南
- Use the STAR method (Situation, Task, Action, Result) to structure your answers. For technical questions, focus on the architectural decisions you made, the trade-offs considered, and the impact on the end-users or business.
- Can you walk us through a project where you evolved a rapid prototype into a production-grade application?
- How do you approach integrating non-deterministic AI components or LLMs into a reliable software system?
- Describe your experience with cloud-native architectures, CI/CD, and ensuring application security.
- How do you balance rapid experimentation with the need for maintainable and scalable code?
- Review modern full-stack development patterns, especially those involving AI/ML integration and cloud-native deployments.
- Prepare specific examples of how you handled ambiguous requirements and translated them into technical implementations.
职位点评
薪资福利85
成长发展90
工作生活75
使命价值95
薪资福利
85较高
Multinational pharma company offers high stability and competitive compensation for senior engineering roles in Israel.
薪资信号偏高 (6千–10万/月)
福利待遇flexible working culture
成长发展
90较高
Role involves cutting-edge AI, LLMs, and agentic workflows in a global R&D team, offering strong technical growth.
技术前沿前沿/新兴技术
技术栈Python、LLM、agentic workflows、cloud-native、CI/CD、containerization
成长机会personal development、career advancement
业务类型ambiguous
工作生活
75中等
Mentions a flexible working culture, but specific WLB policies or remote days are not explicitly detailed in the JD.
工作模式未明确
办公地点未明确
加班情况未提及（无法判断）
工作生活平衡flexible working culture
使命价值
95较高
Directly contributes to healthcare, developing medicines and intelligent devices to improve and prolong patients' lives.
行业发展高速增长赛道
社会影响正向社会影响力较高
使命信号enrich people’s lives、help create, improve and prolong lives、help patients at every stage of life、Sparking Discovery and Elevating Humanity
创新程度积极采用新技术
默克药厂 的其他在招职位
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默克药厂 · Darmstadt, Hessen, GermanyAI 估算 · 8千–1.2万Pharmaceutical Manufacturing Technician Overnight Weekday Shift
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