Principal AI/ML Engineer I (Hybrid – Deerfield, IL)

Walgreens

Deerfield, IL

Job Summary
The Principal AI/ML Engineer is a senior individual contributor responsible for designing and delivering end-to-end artificial intelligence and machine learning solutions with a strong emphasis on agentic AI and integration with enterprise systems. This role focuses on the full lifecycle of AI solutions, including system design, governance, deployment, and operationalization on cloud infrastructure to support scalable and reliable automation of complex business processes.

This position combines deep expertise in classical machine learning with advanced knowledge of large language models (LLMs), agent-based architectures, and multi-agent systems. The Principal AI/ML Engineer designs and develops AI agents capable of interpreting context, planning actions, and executing tasks, and integrates those agents with enterprise platforms, applications, and data sources.

The role partners closely with data scientists, software engineers, platform teams, and business stakeholders to establish technical direction, define best practices, and deliver high-impact AI solutions that support enterprise business objectives.

This role is based in Deerfield, Illinois, and follows a hybrid work schedule requiring four days per week on-site.

Job Responsibilities

Leads in the design and development of complex software that processes, stores and serves data and machine learning models for use by others.
Designs and develops complex and large scale data structures and pipelines to organize, collect and standardize data to generate insights and intelligence to support business needs.
May write complex ETL (Extract / Transform / Load) or ELT processes, designs data stores and develops tools for real-time and offline analytic processing on premise or on cloud infrastructure.
Ensures that data and machine learning pipelines are scalable, repeatable and secure. Improves data consistency, integrity, Dev Ops and ML Ops.
Integrates data from a variety of sources, assuring that they adhere to data quality and accessibility standards.
Designs data infrastructure for scalability, availability, and reliability.
Participates in developing technical / business approaches and new or enhanced technical tools. Recommends the right tool and technology to deliver solutions objectively. Evaluates new technologies for continuous improvement.
Interacts with internal and external peers and management to share highly complex information related to areas of expertise and/or to gain acceptance of new or enhanced technology / business solutions.
Create technical design documents and supporting materials
Provides thought leadership to embrace modern AI/ML, data science and data analytics techniques as critical enablers for business decisions.
Guides and mentors a wide range of audiences.

About Walgreens
Founded in 1901, Walgreens (www.walgreens.com) proudly serves nearly 9 million customers and patients each day across its approximately 8,500 stores throughout the U.S. and Puerto Rico. Walgreens has approximately 220,000 team members, including nearly 90,000 healthcare service providers, and is committed to being the first choice for pharmacy, retail and health services, building trusted relationships that create healthier futures for customers, patients, team members and communities.

Basic Qualifications

Bachelor's degree OR equivalent and at least 8 years of experience in machine learning, software engineering, or data engineering
At least 5 years of experience working with SQL
At least 5 years of experience programming in one or more of the following: Python, C, C++, Spark, Scala, and/or Java
Experience establishing and maintaining key relationships with internal (peers, business partners and leadership) and external (business community, clients and vendors) within a matrix organization to develop strategies that meet department goals within budget and timelines
Experience interacting at the executive level
At least 5 years of experience contributing to financial decisions in the workplace.
At least 5 years of direct leadership, indirect leadership and/or cross- functional team leadership.
Willing to travel up to 10% of the time for business purposes (within state and out of state)

Preferred Qualifications

8+ years of experience in applied machine learning, data science, or machine learning engineering delivering AI/ML solutions for complex business problems.
Demonstrated experience operating as a senior individual contributor responsible for leading complex AI or machine learning initiatives from concept or proposal through production deployment.
Strong background in classical machine learning and statistical modeling with experience applying these methods to large-scale real-world datasets.
Deep hands-on experience working with large language models (LLMs), including prompt engineering, prompt optimization, and techniques used to evaluate and improve model performance.
Understanding of common LLM limitations, including hallucinations and other model failure modes, and familiarity with approaches used to evaluate, monitor, or mitigate these behaviors.
Experience designing or implementing AI agents or agent-based systems capable of interpreting context, planning actions, and executing tasks to automate business workflows.
Experience developing or working with multi-agent systems or agent-based architectures used to coordinate complex AI-driven processes.
Experience integrating LLMs or AI agents with enterprise platforms, internal tools, APIs, or data systems to support automation and decision-support capabilities.
Strong system design and architecture skills for AI and machine learning platforms, including model pipelines, deployment patterns, monitoring, and reliability considerations.
Hands-on experience deploying AI or machine learning workloads on cloud platforms such as AWS, Azure, or Google Cloud.
Familiarity with governance, compliance, and lifecycle management practices associated with production AI and machine learning systems.
Ability to partner effectively with data scientists, engineers, and business stakeholders to drive AI initiatives from concept through delivery.
Strong communication skills with the ability to translate complex business problems into scalable technical solutions and explain AI or machine learning concepts to both technical and non-technical audiences.