AI Solutions Engineer

DLA Piper is, at its core, bold, exceptional, collaborative and supportive. Our people are the backbone, heart and soul of our firm. Wherever you are in your professional journey, DLA Piper is a place you can engage in meaningful work and grow your career. Let’s see what we can achieve. Together. Summary The AI Solutions Engineer is an embedded partner to the Professional Excellence (PE) Practice Group, responsible for intake and shaping of demand into clear problem statements, prioritized backlogs, and sprint-ready user stories. The role collaborates with others to deliver iterative, measurable improvements to PE workflows and solutions, with the goal to help build/deliver re-usable AI engineering patterns that the business uses and accelerate sustainable business workflow automation. This position is designed to support PE’s needs with an understanding of Associate-level work and the practical realities of PE workflow and delivery. Location This position can sit in any of our U.S. offices and offers a hybrid work schedule. Responsibilities PE Intake, Discovery & Problem Framing (Embedded SE/BA) Own requirements intake for PE initiatives; capture a concise problem statement, intended outcomes, and success measures. Engage PE stakeholders to understand workflow pain points and constraints; translate needs into actionable requirements. Apply an understanding of Associate-level work to ensure solutions fit real execution patterns and reduce friction. Agile Backlog Management & User Stories Produce high-quality requirements including functional requirements and user stories suitable for sprint execution. Drive iterative elaboration and refinement with stakeholders and solutions for delivery to maintain a healthy backlog and delivery cadence. Solution Design, Prototyping & Feasibility Evaluate and recommend solutions. Build prototypes / proofs of concept and support iterative refinement to validate feasibility and value. Action solution design and integration planning. Testing, Adoption & Operational Readiness Support UAT planning and execution; translating feedback into backlog updates and improvement cycles. Support rollouts, training materials, demos, and adoption activities in partnership with IT/KM and PE stakeholders. Ensure deliverables meet firm standards for documentation, governance, quality, and supportability. Cross-Functional Delivery Partner with the IT and adjacent teams to surface risks, dependencies, and decisions early and keep delivery moving. Promote consistent delivery practices as the pod model scales across practice/business groups. Desired Skills Background in building AI based solutions within the practice and will be proficient in building AI agents, data integration, using tools to rapidly build pilots/demos and take to production. Understanding of ML models, ability to select the correct models and solution patterns, various RAG patterns (example KG-RAG, Hybrid RAG, Agentic RAG etc.). Experience with variou