Intuitive.ai
Lead Applied Data & AI Engineer (Libertyville)
Intuitive.ai, Libertyville, Illinois, United States, 60092
About us:
Intuitive is an
innovation-led engineering company delivering business outcomes
for 100s of Enterprises globally. With the reputation of being a
Tiger Team
& a
Trusted Partner
of enterprise technology leaders, we help solve the most complex Digital Transformation challenges across following Intuitive Superpowers:
Modernization & Migration Application & Database Modernization Platform Engineering (IaC/EaC, DevSecOps & SRE) Cloud Native Engineering, Migration to Cloud, VMware Exit FinOps
Data & AI/ML Data (Cloud Native / DataBricks / Snowflake) Machine Learning, AI/GenAI
Cybersecurity Infrastructure Security Application Security Data Security AI/Model Security
SDx & Digital Workspace (M365, G-suite) SDDC, SD-WAN, SDN, NetSec, Wireless/Mobility Email, Collaboration, Directory Services, Shared Files Services
Intuitive Services: Professional and Advisory Services Elastic Engineering Services Managed Services Talent Acquisition & Platform Resell Services
About the job: Title:
Lead Applied Data & AI Engineer Start Date:
Immediately # of Positions: 1 Position Type:
Full Time Location : Hybrid in Libertyville, IL, US, 60048
Join our client Global IT Organization as we shape the future through data, analytics, and AI. We are seeking a strategic yet hands-on Lead Applied Data and AI Engineer to design and deliver enterprise-grade data platforms and AI solutions that drive measurable business impact. This role combines deep technical execution with architectural thinkingbuilding robust data lakes, warehouses, and pipelines while operationalizing AI models and intelligent agents using Microsoft Azure AI services and modern frameworks.
Hybrid work:
3 days/week on-site at Libertyville, IL; remaining days remote.
Responsibilities:
Data Engineering & Architecture Design and build data lakes, warehouses, and lakehouse architectures using Microsoft Fabric/OneLake and Azure Data Services. Implement data ingestion, transformation, and orchestration pipelines with strong error handling, logging, and observability. Integrate enterprise systems (SAP S/4HANA, BW, Datasphere) into governed data platforms.
AI Engineering Develop and deploy AI/ML models (LLMs, SLMs, multi-modal, traditional ML) using Python and Azure ML. Build Agentic AI solutions leveraging frameworks like LangChain and Semantic Kernel. Apply RAG patterns and vector databases for retrieval-based AI grounded in curated data.
Operational Excellence Implement MLOps best practices for reproducible, secure deployments using Azure ML and Azure DevOps. Ensure compliance with privacy and regulatory standards (PHI, PII, GDPR, HIPAA). Optimize cost and performance across data and AI workloads.
Collaboration & Leadership Partner with global teams to integrate solutions into enterprise platforms (Power BI, Microsoft Fabric, SAP Datasphere). Mentor junior engineers and promote best practices in data and AI engineering. Contribute to evolving data and AI standards and reusable frameworks.
Essential Functions: Lead hands-on development while applying architectural principles for scalability and governance. Act as a technical thought leader in data-first AI innovation. Navigate ambiguity and make informed decisions balancing data quality, time-to-value, and compliance. Represent client in internal/external forums as a subject matter expert.
Requirements: 812 years experience in data engineering and AI/ML solution delivery. Proven ability to design and implement data platforms and pipelines at enterprise scale. Strong experience with Azure AI/ML tools, Microsoft Fabric, and SAP integration. Bachelors degree in computer science, Information Systems, or related field; masters preferred. Certifications (Azure AI Engineer Associate, Azure Data Scientist Associate) are a plus.
Technical Skills: Advanced Python, ML libraries (PyTorch, TensorFlow, scikit-learn). Expertise in data modeling, governance, and quality frameworks. Familiarity with LangChain, Semantic Kernel, and vector databases. Strong understanding of MLOps, CI/CD, containerization (Docker). Knowledge of Power BI enterprise modeling and Microsoft Fabric medallion architecture.
Preferred Experience in MedTech or regulated healthcare environments. Familiarity with SAP Datasphere and Microsoft Fabric integration patterns.
innovation-led engineering company delivering business outcomes
for 100s of Enterprises globally. With the reputation of being a
Tiger Team
& a
Trusted Partner
of enterprise technology leaders, we help solve the most complex Digital Transformation challenges across following Intuitive Superpowers:
Modernization & Migration Application & Database Modernization Platform Engineering (IaC/EaC, DevSecOps & SRE) Cloud Native Engineering, Migration to Cloud, VMware Exit FinOps
Data & AI/ML Data (Cloud Native / DataBricks / Snowflake) Machine Learning, AI/GenAI
Cybersecurity Infrastructure Security Application Security Data Security AI/Model Security
SDx & Digital Workspace (M365, G-suite) SDDC, SD-WAN, SDN, NetSec, Wireless/Mobility Email, Collaboration, Directory Services, Shared Files Services
Intuitive Services: Professional and Advisory Services Elastic Engineering Services Managed Services Talent Acquisition & Platform Resell Services
About the job: Title:
Lead Applied Data & AI Engineer Start Date:
Immediately # of Positions: 1 Position Type:
Full Time Location : Hybrid in Libertyville, IL, US, 60048
Join our client Global IT Organization as we shape the future through data, analytics, and AI. We are seeking a strategic yet hands-on Lead Applied Data and AI Engineer to design and deliver enterprise-grade data platforms and AI solutions that drive measurable business impact. This role combines deep technical execution with architectural thinkingbuilding robust data lakes, warehouses, and pipelines while operationalizing AI models and intelligent agents using Microsoft Azure AI services and modern frameworks.
Hybrid work:
3 days/week on-site at Libertyville, IL; remaining days remote.
Responsibilities:
Data Engineering & Architecture Design and build data lakes, warehouses, and lakehouse architectures using Microsoft Fabric/OneLake and Azure Data Services. Implement data ingestion, transformation, and orchestration pipelines with strong error handling, logging, and observability. Integrate enterprise systems (SAP S/4HANA, BW, Datasphere) into governed data platforms.
AI Engineering Develop and deploy AI/ML models (LLMs, SLMs, multi-modal, traditional ML) using Python and Azure ML. Build Agentic AI solutions leveraging frameworks like LangChain and Semantic Kernel. Apply RAG patterns and vector databases for retrieval-based AI grounded in curated data.
Operational Excellence Implement MLOps best practices for reproducible, secure deployments using Azure ML and Azure DevOps. Ensure compliance with privacy and regulatory standards (PHI, PII, GDPR, HIPAA). Optimize cost and performance across data and AI workloads.
Collaboration & Leadership Partner with global teams to integrate solutions into enterprise platforms (Power BI, Microsoft Fabric, SAP Datasphere). Mentor junior engineers and promote best practices in data and AI engineering. Contribute to evolving data and AI standards and reusable frameworks.
Essential Functions: Lead hands-on development while applying architectural principles for scalability and governance. Act as a technical thought leader in data-first AI innovation. Navigate ambiguity and make informed decisions balancing data quality, time-to-value, and compliance. Represent client in internal/external forums as a subject matter expert.
Requirements: 812 years experience in data engineering and AI/ML solution delivery. Proven ability to design and implement data platforms and pipelines at enterprise scale. Strong experience with Azure AI/ML tools, Microsoft Fabric, and SAP integration. Bachelors degree in computer science, Information Systems, or related field; masters preferred. Certifications (Azure AI Engineer Associate, Azure Data Scientist Associate) are a plus.
Technical Skills: Advanced Python, ML libraries (PyTorch, TensorFlow, scikit-learn). Expertise in data modeling, governance, and quality frameworks. Familiarity with LangChain, Semantic Kernel, and vector databases. Strong understanding of MLOps, CI/CD, containerization (Docker). Knowledge of Power BI enterprise modeling and Microsoft Fabric medallion architecture.
Preferred Experience in MedTech or regulated healthcare environments. Familiarity with SAP Datasphere and Microsoft Fabric integration patterns.