Sr. Manager Machine Learning & Agent delivery

In this vital role you will join a fun, innovative engineering team within the AI & Data Science (AI&D) - organization. Youll 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 Amgens Applied AI & Automation Footprint.

The Sr Manager Machine Learning & Agent delivery is responsible for driving innovation in AI/ML and agent-based system design at Amgen. This role is integral to advancing the organization's AI strategy by developing intelligent, scalable, and secure multi-agent systems. The Sr Manager Machine Learning & Agent delivery will be responsible for leading technical innovation, mentoring AI/ML teams, and integrating agent-based solutions into enterprise platforms. The ideal candidate has strong experience in design and architecture of AI systems, platforms and cognitive solutions, with excellent communication skills, and a deep understanding of Agile methodologies.

• Play a key role in building and leading a distributed team of Architects, AI/ML Engineers contributing to a growing internal AI & Automation Platforms and Solutions management practice.
• Mentor and provide thought leadership for AI/ML engineers and data scientists, enabling continuous technical growth in agentic design, reinforcement learning, and AI standard methodologies.
• Design, implement, and optimize multi-agent AI/ML systems that enhance automation, decision-making, and system efficiency.
• Define and set the direction for AI/ML frameworks that enable scalable and robust agentic solutions.
• Lead engineering of end-to-end ML pipelines - data ingestion, feature engineering, training, hyper-parameter optimization, evaluation, registration and automated promotion - using Kubeflow, SageMaker Pipelines, Open AI SDK or equivalent MLOps stacks.
• Strong working knowledge of agentic AI or agent-based automation such as AWS BDA, OpenAI, Langchain, Langgraph, UiPath.
• Contribute reusable platform components - feature stores, model registries, experiment-tracking libraries - and evangelize standard processes that raise engineering velocity across global delivery teams.
• Work closely with multi-functional teams to integrate agent-based solutions into Amgens enterprise platforms, aligning AI strategies with business objectives.
• Partner with leadership, product teams, and other collaborators to identify AI opportunities, streamline implementations, and align AI/ML strategies with company goals.
• Ensure that AI solutions meet enterprise-scale performance, security, and reliability standards, while maintaining detailed documentation for long-term scalability.
• Embed security and responsible-AI controls (data encryption, access policies, lineage tracking, explainability and bias monitoring) in partnership with Security, Privacy and Compliance teams.
• Stay at the forefront of emerging trends in agentic automation, autonomous agents, AI orchestration, and GenAI. Evaluate and pilot new tools and frameworks and bring forward innovative capabilities that align with enterprise strategy.
• Conduct market research and competitive analysis to find opportunities and inform product/platforms strategy.

Basic Qualifications:

• Doctorate/Masters/Bachelors degree with 12 - 17 years of experience as Product Owner / Platform Owner / Service Owner.

• Expertise in designing and implementing AI/ML systems and Agents, Agentic Processes.
• Expert knowledge of GenAI tooling: vector databases, RAG pipelines, prompt-engineering DSLs and agent frameworks (e.g., LangChain, Semantic Kernel).
• Proficiency in Python and Java; containerization (Docker/K8s); cloud (AWS, or Azure) and modern DevOps/MLOps (GitHub Actions, Bedrock/SageMaker Pipelines).
• Strong background in authoring and managing highly complex technical documentation at an enterprise level.
• Ability to lead multidisciplinary teams including AI/ML engineers, and architects in a matrixed or agile environment.
• Proven track record selecting and integrating AI SaaS/PaaS offerings and building custom ML services at scale.

• Comprehensive command of machine-learning algorithms - regression, tree-based ensembles, clustering, dimensionality reduction, time-series models, deep-learning architectures (CNNs, RNNs, transformers) and modern LLM/RAG techniques.
• Knowledge in Intelligent Automation with experience in automations tools like UiPath & Power Automate, Process Intelligence tools like Celonis, DocuSign and GenAI Tools/LLMs.
• Knowledge of data privacy, governance, and regulatory requirements (e.g., GxP, HIPAA, GDPR) in deploying AI/automation.
• Experience managing change and driving adoption of new digital technologies across large or regulated enterprises.
• Domain Knowledge in Life Sciences / Healthcare.
• Strong knowledge of Agile methodologies and product management principles.

• Ability to lead, coach, and grow multidisciplinary teams by fostering trust, psychological safety, and a high-performance culture.
• Ability to convey complex AI/ML concepts to both technical and non-technical collaborators.
• Drives transformation by inspiring others, navigating resistance, and building momentum for adopting AI and automation at scale.
• Effectively aligns and motivates multi-functional partners, even in matrixed or decentralized environments.
• Maintains focus and adaptability in a dynamic, fast-evolving tech landscape quickly responding to change while guiding the team with clarity.