Principal Software Engineer

Career Category

Information Systems

Job Description

Join Amgen’s Mission of Serving Patients

At Amgen, if you feel like you’re part of something bigger, it’s because you are. Our shared mission—to serve patients living with serious illnesses—drives all that we do.

Since 1980, we’ve helped pioneer the world of biotech in our fight against the world’s toughest diseases. With our focus on four therapeutic areas –Oncology, Inflammation, General Medicine, and Rare Disease– we reach millions of patients each year. Amgen is advancing a broad and deep pipeline of medicines to treat cancer, heart disease, inflammatory conditions, rare diseases, and obesity and obesity-related conditions. As a member of the Amgen team, you’ll help make a lasting impact on the lives of patients as we research, manufacture, and deliver innovative medicines to help people live longer, fuller happier lives.

Our award-winning culture is collaborative, innovative, and science based. If you have a passion for challenges and the opportunities that lay within them, you’ll thrive as part of the Amgen team. Join us and transform the lives of patients while transforming your career.

Principal Software Engineer 

  

What you will do

Let’s do this. Let’s change the world. In this vital role you will play a pivotal role in building and scaling our machine learning models from development to production. Your expertise in both machine learning and operations will be essential in creating efficient and reliable ML pipelines. A background in data engineering, including experience with data pipelines and distributed data processing, is a strong plus. 

Roles & Responsibilities:  

• Lead the end-to-end design, development, and delivery of machine learning and Generative AI (GenAI) solutions, from problem framing to production deployment and business impact realization.  

• Act as the technical owner for large-scale ML/GenAI initiatives, driving architecture decisions, scalability, reliability, and long-term maintainability.  

• Design and implement advanced agentic AI systems, including multi-agent architectures, reasoning workflows, tool integration, and autonomous decision-making systems.  

• Define and institutionalize evaluation, validation, and governance frameworks for ML/GenAI systems, including model performance, prompt evaluation, safety guardrails, hallucination mitigation, and compliance.  

• Partner directly with business stakeholders and product leaders to understand objectives, translate them into AI/ML solutions, and ensure measurable value delivery.  

• Establish and enforce best practices in MLOps, LLMOps, and DevOps, including CI/CD, monitoring, observability, reproducibility, and cost optimization.  

• Architect and oversee scalable cloud-based ML/GenAI platforms leveraging AWS, GCP, or Azure.  

• Drive experimentation strategy, including A/B testing, prompt optimization, and iterative improvement of models and agent workflows.  

• Provide technical leadership and mentorship to L4 and L5 engineers, including design reviews, code reviews, and career guidance.  

• Lead cross-functional collaboration across data science, engineering, product, and business teams to deliver integrated AI solutions.  

• Stay at the forefront of advancements in machine learning, Generative AI, and agentic systems, and drive adoption of new technologies and approaches.  

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