Hybrid Director, Generative AI – Platform

at Credit Acceptance

• Job title: Director, Generative AI – Platform
• Job type: Full Time
• Experience level: Lead
• Salary: $205,561 - $301,490 per year
• Degree requirement: Postgraduate Degree
• Tech skills: Cloud, Distributed Systems
• Location requirements: Hybrid, Southfield, United States

About the role

• AIML Director responsible for defining AI strategy and leading engineering teams at Credit Acceptance. Driving enterprise-level architecture, operational excellence, and generative AI innovations.

Responsibilities

• Define and communicate the long-term vision for Generative AI and platform capabilities
• Partner with senior executives, product, and engineering leaders to prioritize initiatives and allocate resources effectively
• Lead the enterprise-level architectural design and technical strategy for major components of our generative AI applications and platform
• Partner with senior engineering managers, product leaders, and data scientists / MLEs to translate strategic objectives into executable architectural blueprints
• Drive the adoption of superior engineering standards and advanced AI evaluation frameworks like LangSmith
• Spearhead technical solutioning for the platform's most complex challenges
• Mentor and cultivate a team of associate architects and senior engineers
• Own and execute a significant portion of the technology roadmap
• Oversee design and deployment of enterprise-scale GenAI platforms, inference pipelines, and AI-powered applications
• Ensure operational excellence in LLM Ops, including automation, observability, and lifecycle management
• Champion adoption of cutting-edge generative AI techniques

Requirements

• PhD in Computer Science, AI, or related field with 10+ years in AI/ML engineering (preferred); or MS with 12+ years of experience
• Minimum 5 years in senior leadership roles managing managers and large engineering teams
• Proven track record in building enterprise level production-grade GenAI platforms and services and strong problem-solving skills
• In-depth knowledge and hands-on experience with LLM fine-tuning, model optimization, context graphs, automation, and advanced prompting strategies
• Deep knowledge of LLM lifecycle tools, distributed systems, and cloud-native architectures
• Architect and implement enterprise-grade LLM-powered solutions, managing the full lifecycle from business requirements to production deployment, monitoring, and continuous optimization
• Design and develop multi-agent GenAI systems using state-of-the-art frameworks (LangChain, LlamaIndex) to orchestrate complex workflows across retrieval augmentation, data operations, and compliance verification
• Engineer robust Retrieval Augmented Generation (RAG) pipelines incorporating advanced techniques such as hybrid retrieval, reranking, query expansion, and contextual compression
• Implement parameter-efficient fine-tuning strategies (LoRA, QLoRA, PEFT) to adapt foundation models to domain-specific use cases while optimizing for inference costs and latency
• Develop intelligent routing and orchestration systems to manage conversation state across multiple specialized AI agents, ensuring seamless transitions between different system capabilities
• Build evaluation frameworks to measure and improve LLM performance across diverse metrics, including factuality, coherence, task completion, and alignment with business objectives
• Integrate LLM solutions with existing enterprise architecture, ensuring compliance with data security policies, authentication mechanisms, and transaction safety requirements

Benefits

• Excellent benefits package that includes 401(K) match
• Adoption assistance
• Parental leave
• Tuition reimbursement
• Comprehensive medical/ dental/vision
• Many nonstandard benefits that make us a Great Place to Work