AI Lead

Time Type:
Full time

Worker Type:
Employee

Location:

Chicago

Work Arrangement:
Hybrid

Salary range: $116,000 - $191,500

The purpose of this role is to lead the design, delivery, and enhancement of technical solutions for complex business requirements, ensuring high-quality application support and reporting that meets user specifications. The role involves managing application strategies, roadmaps, and delivery capabilities, as well as providing subject matter expertise and leadership in technical design and issues related to existing applications. Additionally, the role includes mentoring junior developers, driving user acceptance testing, and actively engaging with business stakeholders to influence the adoption of solutions.

• AI Strategy & Leadership:
  Lead the design, architecture, and deployment of enterprise AI and Generative AI solutions aligned with business and technology priorities.
• Partner with Product, Technology, Data, Security, Architecture, and Business leaders to identify and deliver high-value AI opportunities.
• Provide technical leadership, coaching, and mentorship across AI delivery teams.
• Establish scalable AI patterns, standards, and best practices across the organization.
• Drive AI innovation while balancing business value, risk, security, and operational considerations.

• Architect and deliver AI solutions built on the Microsoft Azure AI platform, including:
• Azure AI Foundry
• Azure OpenAI Service
• Azure AI Search
• AI Agents and Agentic Workflows
• Retrieval Augmented Generation (RAG)
• Prompt Engineering
• Model Evaluation & Observability

• Build scalable solutions that integrate enterprise data sources, APIs, and business systems.
• Lead solution design reviews and transform architectural feedback into pragmatic, production-ready designs.
• Establish reusable AI frameworks and accelerators that can be leveraged across multiple business domains.

• Evaluate, select, and operationalize leading foundation models based on business use cases.
• Implement solutions using models hosted within Azure AI Foundry and Azure AI services.
• Work with multiple LLM providers including:
  OpenAI GPT, Anthropic Claude, Google Gemini, Microsoft Copilot ecosystem, Emerging enterprise AI platforms.
• Understand trade-offs between performance, cost, latency, governance, and business outcomes.

• Partner closely with Cyber Security, Enterprise Architecture, Infrastructure, Networking, and Risk teams.
• Design AI solutions that meet enterprise security, privacy, compliance, and governance standards.
• Navigate architecture review boards and security approval processes.
• Develop and advocate for approved AI patterns, reference architectures, and governance frameworks.
• Ensure Responsible AI principles are embedded across solution design and delivery.

• Rapidly prototype new concepts and proof-of-concepts to validate emerging opportunities.
• Drive successful transition from experimentation to enterprise-scale implementation.
• Act as a change agent, helping teams adopt modern AI capabilities and ways of working.
• Influence and align stakeholders across multiple teams, business units, and technology functions.

• Deep experience designing and deploying enterprise AI and Generative AI solutions.
• Strong hands-on experience with Azure AI Foundry, Azure OpenAI Services, RAG architectures, Agentic AI solutions, Prompt Engineering techniques, LLM evaluation frameworks, API integrations and cloud-native architectures.
• Experience with multiple LLM providers such as OpenAI, Anthropic Claude, and Google Gemini.
• Strong software engineering background with proficiency in Python.
• Familiarity with data science methodologies and machine learning fundamentals.
• Understanding of vector databases, embeddings, semantic search, and knowledge retrieval architectures.

• Experience working with modern enterprise delivery toolsets, including Azure Dev Ops, Git Hub, Git Hub Copilot, Jira, Service Now, CI/CD and Dev Ops practices.

• Strong understanding of enterprise application architecture.
• Working knowledge of networking concepts, cloud connectivity patterns, APIs, authentication, and security controls.
• Experience collaborating with infrastructure, networking, cybersecurity, and enterprise architecture teams.
• Ability to evolve solution designs based on architecture and security review…