AI Solutions Architect

We’re looking for an AI Solutions Architect (Forward Deployed Engineer) to design, build, and validate AI-driven experimentation and decisioning systems across digital commerce experiences. This role blends solution architecture, AI engineering, and validation, ensuring that LLM and agent-driven systems are production-ready, accurate, and measurable while powering personalization, experimentation, and real-time decisioning. What You’ll Do Design and deliver AI-driven experimentation and decisioning platforms across digital channels Build systems supporting personalization, targeting, and real-time experience optimization (A/B, multi-variant, bandits) Embed LLMs and ML models into production workflows powering customer-facing experiences Architect API-driven services enabling real-time decisioning at scale Design and implement evaluation frameworks for LLM and agent-based systems Build automated validation pipelines for regression testing, prompt comparison, and continuous model evaluation Define and track metrics for model performance, experimentation outcomes, and business impact Implement observability and human-in-the-loop workflows to monitor and improve AI system behavior What You Bring 8+ years of experience in solution architecture, software engineering, or AI/ML systems Proven experience building and validating production AI/LLM systems Strong experience with experimentation frameworks (A/B testing, personalization, optimization) Hands-on experience with LLM integration, prompt design, and evaluation strategies Experience designing AI validation frameworks and model evaluation pipelines Strong backend experience with Node.js and API-driven architectures Python experience for data pipelines, ML integration, or evaluation workflows Exposure to React or frontend integration concepts Nice to Have Experience with RAG systems, grounding strategies, or vector databases Familiarity with LLM orchestration frameworks (LangChain, LangGraph) Experience with multi-arm bandits, recommendation systems, or segmentation models Exposure to AI observability (latency, cost, drift, tracing) Experience with Azure data platforms (Synapse, data lakes) or similar Why Join Work on AI-driven experimentation and real-time decisioning at enterprise scale Own both system design and validation of AI/LLM-powered experiences Direct impact on personalization, customer experience, and ecommerce growth Collaborate across product, data, and engineering teams in a fast-moving environment Show more Show less