Remote Position
[Remote] Sr. Manager, AI Engineering
🌍 Remote · United States
💼 Full-time
Note: The job is a remote job and is open to candidates in USA. Deckers Brands is committed to creating an inclusive workplace where employees can bring their authentic selves and make a positive impact. The Sr. Manager, AI Engineering will lead the enterprise AI engineering capability, oversee governed AI platforms and reusable patterns, and deliver responsible AI applications into production. The role also manages AI engineering teams, production readiness, evaluation, monitoring, and cross-functional AI initiatives.
Responsibilities
- Own the enterprise AI platform, including governed access to foundation models, unified gateway, model routing, prompt and context management, and cost controls
- Define and maintain reusable AI engineering patterns for retrieval augmented generation, agents, orchestration, and LLM application architecture
- Lead the evaluation framework for AI systems, including offline evaluation suites, online quality monitoring, regression testing, and acceptance criteria for release
- Deliver AI applications into production across customer-facing and internal use cases, from proof of concept through governed deployment and ongoing operation
- Manage operational quality for production AI systems, including latency, availability, cost per interaction, quality regression detection, and support coverage
- Track the foundation model and AI tooling landscape, evaluate new capabilities, and manage migration as models and providers change
- Own the AI engineering roadmap and staffing plan, translating enterprise and brand priorities into a sequenced delivery plan
- Manage and mentor AI engineers, direct external AI delivery partners, and supply AI engineering capability into cross-functional teams
- Establish production readiness bar for AI systems, including guardrails, safety controls, human-in-the-loop design, fallback behavior, and incident response
- Implement responsible AI policy as engineering controls, including model risk documentation, evaluation evidence, output monitoring, and audit trails
- Partner with business, digital, data, ML engineering, enterprise architecture, security, privacy, and infrastructure teams to identify, scope, and prioritize AI use cases
Skills
- Interested applicants must reside in one of the following approved states: Arizona, California, Colorado, Indiana, Massachusetts, Minnesota, New York, Oregon, Pennsylvania, Texas, Utah, Washington
- Bachelor's degree required, preferably in Computer Science, Engineering, or a related technical field
- 8–12 years of software, data, or machine learning engineering experience building production systems
- 3–5+ years leading engineering teams in cloud-native environments
- 3+ years delivering production AI or machine learning systems, including 2+ years building generative AI or large language model applications
- Demonstrated experience taking generative AI from proof of concept into governed production, including evaluation, guardrails, and monitoring
- Hands-on experience with retrieval augmented generation, agent frameworks, tool use, and orchestration patterns
- Experience with foundation model platforms such as AWS Bedrock, Azure OpenAI, or equivalent
- Deep understanding of large language model application architecture, including retrieval, context management, tool use, agent design, and orchestration
- Strong grasp of AI evaluation methods, safety and security concerns, and cost awareness for AI systems
- Strong leadership and people-management skills with a focus on coaching and developing talent
- Excellent problem-solving, analytical thinking, and decision-making skills
- Strong communication and influencing skills across technical and business stakeholders
- Comfortable working in a fast-paced, matrixed, and global environment
- Master's degree preferred
Benefits
- Competitive bonuses and compensation programs that reward success and support career development
- Financial planning programs to protect income, pay for expenses, and invest in the future
- Time away from work to support family needs, health, and recharging
- Generous employee discounts
- Community-based programs
- Extensive opportunities and support for personal and professional development
- Comprehensive health and wellness programs and offerings
- Remote work arrangement
Company Overview
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