Position: Senior AI Technical Architect
Location: Westchester, IL (Hybrid)
Engagement: 12 months, extendable
Start Date: Early October 2026
Experience: 15+ years in enterprise technology, with significant experience in AI/ML, GenAI, and enterprise architecture
THE OPPORTUNITY
We are seeking a Senior AI Technical Architect to lead the architecture, governance, and delivery of enterprise-scale AI and GenAI solutions. This is a senior client-facing role responsible for transforming a large portfolio of AI opportunities into a governed, value-driven, production-ready AI roadmap.
The architect will build upon Ingredion's existing AI initiatives, including Ask Ingredion, manufacturing AI/ML capabilities, Microsoft technologies, SAP, and enterprise analytics platforms. The role will partner closely with business, technology, enterprise architecture, security, and executive stakeholders to identify high-value AI opportunities, establish technical and governance standards, and guide distributed engineering teams through implementation.
The ideal candidate combines deep technical expertise in AI/ML and GenAI with strong enterprise architecture, governance, stakeholder management, and delivery leadership capabilities.
KEY RESPONSIBILITIES
- AI Strategy & Portfolio Leadership
- Assess and prioritize a portfolio of approximately 150 AI opportunities based on business value, technical feasibility, risk, complexity, cost, and time-to-value.
- Lead rapid 4 6-week AI discovery and assessment engagements for multiple high-priority use cases.
- Translate business opportunities into a structured, funded AI delivery roadmap.
- Establish a scalable framework for identifying, evaluating, prioritizing, and industrializing AI use cases.
- Partner with executive sponsors to communicate portfolio progress, investment requirements, risks, and business outcomes.
- Enterprise AI Architecture
- Define end-to-end enterprise AI architecture covering application, data, integration, AI/ML, security, infrastructure, and observability layers.
- Design scalable AI solutions using an Azure-centric technology ecosystem, integrating with Microsoft 365 Copilot, Teams, Azure AI services, SAP, Power BI, and enterprise APIs.
- Architect solutions leveraging LLMs, RAG, agentic AI, AI orchestration, intelligent automation, and enterprise integration patterns.
- Establish reusable architecture patterns for Assist, Act, and Decide agent models.
- Evaluate emerging AI technologies and platforms while maintaining a strong focus on enterprise standards, interoperability, security, and total cost of ownership.
- Minimize unnecessary introduction of new technology and identify capability gaps where new platforms or tooling provide measurable value.
- Technical Leadership & Delivery
- Provide technical direction and architectural oversight to distributed engineering teams and offshore delivery pods.
- Establish technical standards, coding and architecture guidelines, reusable components, reference implementations, and engineering best practices.
- Conduct architecture reviews, design reviews, technical assessments, and production-readiness reviews.
- Guide teams through complex technical challenges and remove architectural and engineering blockers.
- Ensure solutions meet enterprise requirements for scalability, reliability, security, performance, maintainability, and operational readiness.
- Establish a repeatable AI delivery "factory" model that accelerates the transition from validated use cases to production.
- AI/GenAI Technical Expertise
- Provide hands-on architectural leadership across:
- Large Language Models (LLMs)
- Generative AI
- Agentic AI
- Retrieval-Augmented Generation (RAG)
- AI agents and multi-agent architectures
- AI orchestration
- Prompt engineering
- Model evaluation
- Vector databases and semantic search
- Enterprise API integration
- AI application security
- Observability and tracing
- Demonstrate strong experience with Azure OpenAI, Azure AI Foundry, Microsoft Copilot ecosystem, or comparable enterprise AI platforms.
- Define patterns for integrating AI capabilities with enterprise systems such as SAP, Microsoft 365, Teams, Power BI, and other business applications.
- Stakeholder & Executive Management
- Act as the senior technical advisor and trusted AI architecture partner to business and technology leadership.
- Facilitate workshops with stakeholders across manufacturing, supply chain, finance, quality, operations, IT, and corporate functions.
- Translate complex AI and technology concepts into clear business outcomes and executive-level recommendations.
- Manage competing priorities and align business, technology, security, architecture, and delivery teams.
- Present architecture decisions, investment recommendations, risks, dependencies, and progress to senior leadership.
- Build strong relationships with executive sponsors, product owners, enterprise architects, engineering leaders, and external partners.
- Value Realization & Adoption
- Define measurable success criteria for AI initiatives, including adoption, productivity, quality, cost savings, cycle-time reduction, and business ROI.
- Establish mechanisms to track AI solution performance and business outcomes after production deployment.
- Partner with business owners to drive adoption and organizational change.
- Ensure AI solutions deliver measurable business value rather than remaining technology prototypes.
WHAT YOU BRING
Required Experience
- 15+ years of overall experience in enterprise technology, software engineering, solution architecture, or technical consulting.
- 5+ years of experience in AI/ML, Generative AI, intelligent automation, or AI-enabled enterprise solutions, with progressively increasing technical leadership responsibilities.
- Proven experience as a Technical Architect, Enterprise Architect, Solution Architect, AI Architect, or equivalent senior technology leadership role.
- Strong experience designing and delivering complex, enterprise-scale technology solutions.
- Demonstrated experience establishing AI architecture, governance, security, and operational standards.
- Strong hands-on understanding of LLMs, RAG, Agentic AI, AI orchestration, evaluation frameworks, and enterprise AI integration.
- Experience with Azure OpenAI, Azure AI Foundry, Microsoft AI ecosystem, or comparable enterprise AI platforms.
- Strong understanding of enterprise integration patterns, APIs, cloud architecture, data platforms, identity, security, and observability.
- Experience leading distributed/offshore engineering teams across multiple time zones.
- Proven experience working directly with senior business, technology, security, and executive stakeholders.
- Strong ability to balance business value, technical feasibility, risk, cost, scalability, and time-to-market.
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