Manager, Generative AI Engineering Location: Remote (U.S.) Salary Range: $120k to $170k About the Role We are looking for a Manager of Generative AI Engineering to lead a high-performing team while remaining deeply hands-on in building production-grade AI systems. This is a hybrid leadership role (~50/50 split) combining technical execution with people management. Youll play a critical role in shaping our AI capabilities, delivering scalable solutions, and fostering engineering excellence across the team. What Youll Do
Lead and manage a team of ~710 engineers, driving performance, growth, and delivery quality
Contribute directly to the design and development of generative AI systems, including agentic workflows, multi-step RAG pipelines, and LLM-powered applications
Translate stakeholder needs into well-defined engineering work with clear scope, tradeoffs, and acceptance criteria
Own delivery execution, including sprint planning, backlog management, and removing blockers
Coach and mentor engineers through hands-on support, pairing, and code reviews
Ensure production system performance across reliability, scalability, latency, and cost efficiency
Partner with product, data, and platform teams to align engineering efforts with broader AI strategy
Communicate technical concepts, risks, and progress to both technical and non-technical stakeholders
Develop reusable engineering patterns for prompt management, orchestration, structured outputs, and workflow versioning
Implement evaluation frameworks for LLM outputs, including regression testing and failure analysis
Establish safeguards such as human-in-the-loop processes, schema validation, and output controls
Ensure AI systems are secure against prompt injection, data leakage, and unauthorized access
Continuously evaluate emerging AI tools, models, and architectures to improve system performance
Foster a fast-paced, iterative development culture with continuous feedback and improvement
Required Qualifications
Proven experience delivering production LLM or generative AI systems
Strong expertise in model selection, prompt design, orchestration, and system tradeoffs
Experience building evaluation pipelines and quality frameworks for AI outputs
Solid background in distributed systems and production software engineering
Demonstrated progression into technical leadership (engineering management or senior IC roles)
Experience mentoring engineers and raising technical standards across teams
Ability to break down ambiguous problems into structured, executable solutions
Experience integrating AI systems with enterprise data, APIs, and security requirements
Bachelors degree in a technical field or equivalent practical experience
Preferred Qualifications
Experience in domains such as product data, ERP, ecommerce, or analytics platforms
Familiarity with modern data architectures and pipeline patterns
Experience with agent-based systems and advanced RAG implementations
Experience with cloud-native systems, APIs, and event-driven architectures
Exposure to responsible AI practices and governance frameworks
Experience with common AI development tools and frameworks (e.g., Python-based services, containerization, APIs)