Sr Associate Applied AI Solution Architect (Agentic Automation, GenAI & ML)

Career Category

Information Systems

Job Description

ABOUT AMGEN

Amgen harnesses the best of biology and technology to fight the world’s toughest diseases, and make people’s lives easier, fuller and longer. We discover, develop, manufacture and deliver innovative medicines to help millions of patients. Amgen helped establish the biotechnology industry more than 40 years ago and remains on the cutting-edge of innovation, using technology and human genetic data to push beyond what’s known today.

ABOUT THE ROLE

Role Description:

The Sr Associate Solution Architect position offers a unique opportunity to join a fun, innovative engineering team within the AI & Data Science (AI&D) - organization. You’ll work on next-generation capabilities and services in Applied AI & Automation using innovative COTS products, open-source software, frameworks, tools, and cloud computing services. The role also emphasizes demonstrating these capabilities to support critical business operations and initiatives, in ensuring quality, compliance, and performance across Amgen’s Applied AI & Automation Footprint.

Role Summary

We are seeking a highly skilled and innovative Senior Associate Solution Architect to design, build, and scale enterprise-grade AI systems, with a strong emphasis on agentic AI, intelligent automation, and MLOps best practices. This role is ideal for a hands-on architect who operates at the intersection of autonomous AI systems, cloud-native platforms, and regulated enterprise environments.

The architect will lead the design of agent-based systems capable of autonomous planning, tool use, multi-agent coordination, and integration with enterprise automation platforms.

Key Responsibilities

• Architect, build, and deploy full-stack AI and agentic systems with a focus on scalability, reliability, and cost efficiency.
• Design and implement agentic AI solutions that autonomously plan, execute, and monitor complex workflows using LLMs, multi-agent patterns, and tool orchestration.
• Define reference architectures for agent-based automation across a maturity spectrum, from basic agentic workflows to advanced multi-agent systems integrated with enterprise platforms.
• Integrate agentic AI with intelligent automation and RPA platforms such as UiPath and Power Automate to enable end-to-end business process automation.
• Collaborate with data scientists, engineers, and product teams to drive platform reuse, architectural consistency, and innovation.
• Establish MLOps and AgentOps practices including CI/CD, monitoring, governance, and lifecycle management for AI and agent-based systems.
• Stay current with advancements in generative AI, multi-modal models, and agent frameworks, applying them pragmatically in enterprise contexts.

Basic Qualifications

• Bachelor's degree with 4 to 8 years of experience, or Master's degree, in Life Sciences, Biotechnology, Pharmacology, Information Systems, or related fields.
• 3+ years of hands-on experience designing and deploying AI/ML systems in production environments.
• Demonstrated experience architecting agentic AI systems, including multi-agent coordination, tool integration, and autonomous workflow execution.
• Strong proficiency in Python and ML frameworks such as TensorFlow or PyTorch.
• Experience with cloud platforms such as AWS, Azure, or GCP.
• Hands-on experience with MLOps practices and AI model lifecycle management.
• Solid understanding of LLM-based architectures, prompt engineering, and fine-tuning techniques.
• Experience designing and deploying automation workflows using platforms such as UiPath and Power Automate.

Preferred Qualifications

• Experience with agentic AI frameworks and orchestration patterns, for example LangChain, LangGraph, AWS AgentCore, UiPath Agent or Maestro, N8N, and A2A.
• Good understanding of Model Context Protocol (MCP) concepts and application patterns.
• Experience with vector databases and retrieval-augmented generation (RAG) architectures.
• Experience architecting and deploying end-to-end ML pipelines using platforms such as Kubeflow, Amazon SageMaker, or OpenAI SDK.
• Strong understanding of cloud-native optimization, CI/CD pipelines, observability, and governance.
• Experience with model monitoring, observability tools, and responsible AI practices.
• Familiarity with SAP platforms, preferably S4 and Build Process Automation (BPA).
• Experience in Pharma, Biopharma, or regulated healthcare environments.

Soft Skills

• Strong solution design and analytical problem-solving skills.
• Ability to translate complex business requirements into scalable technical architectures.
• Excellent communication, collaboration, and presentation skills.
• Proven ability to work effectively in cross-functional, team-based environments.

EQUAL OPPORTUNITY STATEMENT

Amgen is an Equal Opportunity employer and will consider you without regard to your race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, or disability status.

We will ensure that individuals with disabilities are provided with reasonable accommodation to participate in the job application or interview process, to perform

.