Principal Architect

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 Architect

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.

• Lead the end-to-end design, development, and delivery of machine learning and Generative AI (GenAI) solutions, leveraging Databricks, Apache Spark, SQL, and Python for scalable data processing, feature engineering, and model development from problem framing to production deployment and business impact realization.
• Act as an Architect for large-scale Data Engineering and ML/GenAI initiatives, driving architecture decisions across lakehouse platforms (Databricks), distributed compute (Spark), and cloud ecosystems (AWS/GCP/Azure) to ensure scalability, reliability, and long-term maintainability.
• Design and implement advanced data pipelines and AI systems, including batch and streaming data processing (Spark), data modeling (SQL), and ML workflows (Python), along with multi-agent architectures, reasoning workflows, tool integration, and autonomous decision-making systems.
• Build and optimize robust data foundations for AI by developing high-quality, scalable ETL/ELT pipelines in Databricks, ensuring data availability, consistency, and performance for downstream ML/GenAI use cases.
• Define and institutionalize evaluation, validation, and governance frameworks for ML/GenAI systems, including model performance tracking, prompt evaluation, safety guardrails, hallucination mitigation, and compliance.
• Partner directly with business stakeholders and product leaders to translate objectives into data-driven AI/ML solutions, ensuring measurable value through well-defined data pipelines, KPIs, and experimentation frameworks.
• Establish and enforce best practices in MLOps, LLMOps, DataOps, and DevOps, including CI/CD pipelines, Databricks workflows, monitoring, observability, reproducibility, and cost optimization.
• Architect and oversee scalable cloud-based data and AI platforms, integrating Databricks Lakehouse, Spark processing layers, and cloud-native services for unified analytics and AI workloads.
• Drive experimentation strategy, including A/B testing, prompt optimization, and data-driven iteration, leveraging SQL analytics and Python-based experimentation frameworks.
• Provide mentorship to L4 and L5 engineers in data engineering (Spark, SQL, Databricks) and AI/ML development (Python, GenAI frameworks), including design reviews, code reviews, and career guidance.
• Lead cross-functional collaboration across data engineering, data science, platform engineering, and business teams to deliver integrated, production-grade AI solutions.
• Stay at the forefront of advancements in data engineering (Spark ecosystem, lakehouse architectures) and Generative AI/agentic systems, driving adoption of new technologies and best practices.

What we expect of you

We are all different, yet we all use our unique contributions to serve patients. The professional we seek is a Principal Architect with these qualifications.

Basic Qualifications

Doctorate degree and 2 years of experience

OR

Master’s degree and 4 years of experience

OR

Bachelor’s degree and 6 years of experience

OR

Associate’s degree and 10 years of experience

OR

High school diploma / GED and 12 years of experience

Preferred Qualifications

• Deep expertise in machine learning, deep learning, and Generative AI (LLMs, transformers, embeddings, fine-tuning techniques).

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