Kelly Science, Engineering, Technology & Telecom is seeking an experienced AI Solutions Architect to help launch and scale their enterprise AI capabilities. This hands-on, high-impact role involves designing, prototyping, and guiding the delivery of AI solutions that address real business problems.
Responsibilities:
- Design and define end-to-end AI solution architecture for enterprise use cases
- Partner with stakeholders to translate business needs into AI-driven solutions
- Build or guide development of rapid POCs to validate feasibility and value
- Leverage Azure AI Foundry and LLM-based services to develop scalable solutions
- Establish best practices for AI system design, including:
- Prompt engineering
- Evaluation and monitoring
- Human-in-the-loop workflows
- Collaborate with engineering teams to productionize solutions
- Provide technical leadership in shaping the AI roadmap and strategy
- You will focus on delivering solutions that support internal business teams, including:
- Customer Service / Order Processing
- Parse and extract structured data from customer purchase orders (POs)
- Process unstructured inputs (emails, PDFs, documents)
- Integrate outputs into ERP systems
- Supply Chain & Inventory Optimization
- Develop recommendation engines for inventory movement and allocation
- Optimize distribution networks and stock levels
- Support decision-making with AI-driven insights
Requirements:
- 3+ years of experience in AI/ML, with strong emphasis on applied/production use cases
- Proven experience designing end-to-end AI or data-driven systems
- Hands-on experience with LLMs / Generative AI solutions
- Familiarity with Azure AI ecosystem (Azure AI Foundry, Cognitive Services, etc.)
- Strong understanding of data pipelines and system integration
- Strong understanding of APIs and microservices architectures
- Strong understanding of structured and unstructured data processing
- Ability to balance architecture design with hands-on development
- Experience with document intelligence / NLP / extraction use cases
- Background in supply chain, ERP, or enterprise systems integration
- Exposure to recommendation systems or optimization models
- Experience building POCs and scaling to production systems