Job Summary The Principal Machine Learning Engineer will serve as a principal technical authority for Machine Learning and GenAI initiatives, providing strategic direction across architecture, system design, and long-term AI strategy. The role requires deep expertise in Machine Learning and Artificial Intelligence engineering, strong software engineering foundations, and extensive experience with backend systems, APIs, data-driven architectures, and complex or legacy environments. The engineer will evaluate existing platforms, lead proof-of-concept initiatives, make high-impact architectural decisions, and bridge current system architectures with future-state AI/ML capabilities. Key Responsibilities • Serve as the principal technical authority for Machine Learning and GenAI initiatives. • Define and communicate technical roadmaps, architectural direction, and long-term AI strategies. • Evaluate legacy systems and platforms to identify technical constraints, risks, and modernization opportunities. • Make high-impact technical decisions that guide engineering teams and influence the evolution of platforms. • Lead and design proofs of concept (POCs) to validate new ML/GenAI approaches, tools, and architectures. • Assess the feasibility, scalability, and integration considerations of AI solutions before broader adoption. • Translate experimental results into clear architectural recommendations and actionable next steps. • Develop a deep understanding of existing backend systems, data flows, APIs, and legacy codebases. • Bridge historical system architecture with future-state AI/ML capabilities. • Partner closely with engineering teams to ensure strategic technical decisions are practical and aligned with implementation realities. Required Qualifications • 10+ years of relevant experience, ideally progressing from software engineering into ML Engineering or GenAI Engineering. • Extensive expertise in Machine Learning and Artificial Intelligence engineering. • Strong foundation in Python and/or Java. • Strong architecture and system design experience, with the ability to define end-to-end technical strategies. • Demonstrated technical thought leadership and experience driving architectural decisions. • Deep understanding of backend engineering, system design, APIs, data-driven architectures, and complex or legacy systems. Preferred Qualifications • Experience with Go or other modern software engineering languages.