AI/ML Engineer

What Data Science contributes to Cardinal Health

The Data & Analytics Function oversees the analytics life-cycle in order to identify, analyze and present relevant insights that drive business decisions and anticipate opportunities to achieve a competitive advantage. This function manages analytic data platforms, the access, design and implementation of reporting/business intelligence solutions, and the application of advanced quantitative modeling.

Data Science applies base, scientific methodologies from various disciplines, techniques and tools that extracts knowledge and insight from data to solve complex business problems on large data sets, integrating multiple systems.
Job Overview

We are seeking a product-oriented AI/ML Engineer who partners with product managers, software engineers, data engineers, and business stakeholders to design and deliver enterprise-scale Generative AI solutions. In this role, you will be hands-on in the development of AI-powered applications, including Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, intelligent automation workflows, and conversational experiences.

The ideal candidate combines strong software engineering fundamentals with expertise in modern AI technologies and cloud-native application development. You will be responsible for transforming business problems into scalable AI solutions, building production-grade ML systems, integrating AI capabilities into enterprise platforms, and ensuring solutions are secure, reliable, and measurable.

This role is ideal for an engineer who enjoys working across the full lifecycle of AI products, from experimentation and prototyping to deployment, monitoring, optimization, and business adoption.
Qualifications

- 4-8yearsofexperienceinSoftwareEngineering,MachineLearningEngineering,AIEngineering,orrelatedfieldspreferred.

- Bachelor'sdegreeinComputerScience,Engineering,DataScience,ArtificialIntelligence,orrelateddiscipline;equivalentexperienceconsidered.

- StrongproficiencyinPythonandexperiencedevelopingproduction-gradeapplications.

- ExperiencebuildingRESTAPIsusingframeworkssuchasFastAPI,Flask,orsimilartechnologies.

- ExperienceworkingwithinAgileandSDLCframeworks.

- ExperienceusingGitHubandCI/CDplatforms(GitHubActions,GitLab,AzureDevOps,Jenkins,Harness,etc.).

- ExperiencecontainerizingapplicationsusingDocker.

- ExperiencedeployingandmanagingworkloadsonKubernetesplatforms(GKE,AKS,EKS,OpenShift,etc.).

- ExperienceworkingwithcloudplatformssuchasGoogleCloudPlatform(GCP),Azure,orAWS.

Requirements

- ExperiencedesigningandimplementingGenerativeAIsolutionsusingLargeLanguageModels(OpenAI,Gemini,Claude,Llama,Mistral,orsimilar).

- StrongunderstandingofRetrieval-AugmentedGeneration(RAG)architectureandvectordatabases.

- ExperiencebuildingAIAgentsandmulti-agentworkflowsusingframeworkssuchasLangGraph,LangChain,CrewAI,SemanticKernel,orequivalent.

- ExperienceintegratingAIservicesthroughAPIsandenterprisesystems.

- Knowledgeofpromptengineering,evaluationframeworks,andAIapplicationoptimizationtechniques.

- FamiliaritywithMLOpsandLLMOpsconcepts,includingmodeldeployment,monitoring,observability,andgovernance.

- ExperienceimplementingresponsibleAI,security,privacy,andcompliancecontrolsforenterpriseAIsolutions.

- AbilitytodevelopscalableAIsolutionsusingcloud-nativearchitecturesandevent-drivenpatterns.

- ExperienceworkingwithrelationalandNoSQLdatabases.

- Strongunderstandingofsoftwaredesignpatterns,testingstrategies,andproductionsupportpractices.

- ProvenabilitytocollaborateeffectivelywithproductteamstotranslatebusinessrequirementsintoAI-poweredsolutions.

- Excellentcommunicationskillswiththeabilitytoexplaintechnicalconceptstobothtechnicalandnon-technicalaudiences.

What is expected of you and others at this level

- Applies comprehensive knowledge and a thorough understanding of concepts, principles, and technical capabilities to perform varied tasks and projects

- May contribute to the development of po