Lead AI Engineer, Business Operations

Establishes the architectural patterns, evaluation practices, and deployment standards for the team Makes framework and model recommendations that set the foundation for the team Collaborates with the AI Enablement Manager and business unit to optimize operational processes, owning the infrastructure architecture and translating strategic direction into technical plans, product life cycles, a prioritized backlog, and buildable work Owns solutions end-to-end: technically planning, architecture, build, and deployment, then continuously monitors, iterates, and improves them to keep them reliable in production Partners with data governance to ensure solutions meet compliance, data quality, and operational standards Builds and continuously maintains the monitoring, evaluation, and regression detection systems that keep production agents reliable over time, including logging, performance benchmarking, and feedback loops that surface drift early. Leads the team as it grows, onboarding new team members like AI Product Manager and AI Operations Specialists for intake, sequencing, stakeholder coordination, and product ownership of deployed solutions. Requirements Bachelor's degree in Computer Science or related field, or equivalent experience 5+ years of software engineering and architecture experience with a strong full-stack foundation — backend services, API design, system integration, and data infrastructure Recent hands‑on experience architecting and delivering AI or LLM‑backed systems in production Experience architecting solutions from scratch and owning them through deployment, observability, testing, and ongoing reliability Experience with AI development practices — model selection, fine‑tuning, prompt engineering, evaluation frameworks, and understanding when each approach is the right fit Proficiency in Python; experience with cloud platforms Experience mentoring engineers and setting technical direction across multiple initiatives Strong communication skills with both technical and non‑technical stakeholders. Core Competencies Demonstrates expertise in software engineering and architecture, with a strong focus on AI and LLM‑backed systems. Capable of leading teams, optimizing operational processes, and ensuring compliance and reliability in production environments. Highest-signal resume keywords Software Engineering Experience AI Development Practices Python Proficiency Full‑Stack Architecture Team Leadership ATS Optimization Keywords Hard Skills Software Engineering Architecture API Design System Integration Data Infrastructure AI Systems Architecture Model Selection Fine‑Tuning Prompt Engineering Testing Soft Skills Strong Communication Skills Mentoring Certifications & Qualifications Bachelor's Degree in Computer Science Industry Keywords AI Enablement Data Governance Operational Standards Monitoring Systems Production Reliability Tools & Technologies Cloud Platforms #J-18808-Ljbffr Jobtailor