Director, Data Engineering & AI

Salary: $137000 - 146000 per year Requirements: Expert-level proficiency in modern data engineering tools and languages, including Python, SQL, Spark, streaming technologies such as Kafka, orchestration platforms, and cloud data environments such as Snowflake and Azure. Proven, hands-on experience building and deploying machine learning models and generative AI or large language model applications into production. Practical experience with MLOps, including CI/CD pipelines, containerization, automated testing, and model monitoring. Broad enterprise data experience across complex domains such as financial, labor and workforce, IoT or sensor, employee activity, and client or operational data. Demonstrated success delivering AI products with measurable business impact. Strong technical leadership background, including experience building and scaling delivery-focused engineering teams. Current, recent history as a top individual technical contributor with sustained hands-on coding and problem-solving. Ability to move fluidly between direct technical execution and strategic leadership, including roadmap ownership, architecture decisions, and executive communication. Bachelors degree in Computer Science, Engineering, Data Science, or a related field; advanced degree in a quantitative discipline is preferred. At least 7 years of data and software engineering experience, including 4 years developing AI or ML solutions and 2 years in engineering leadership roles. Responsibilities: Architect and build production-grade batch and streaming data pipelines for high-priority and high-ambiguity initiatives across financial, workforce, sensor, employee, and client data. Personally design, prototype, develop, and deploy machine learning models and generative AI applications, especially for new or unproven use cases. Stay deeply involved in production systems by debugging critical issues, reviewing high-stakes code and model logic, and serving as a trusted technical authority. Define and execute the AI and machine learning roadmap for the line of business, identifying impactful use cases such as predictive maintenance, forecasting, workforce optimization, analytics, and intelligent reporting. Oversee enterprise data architecture standards, design patterns, and modeling principles to ensure alignment across engineering, AI, and vendor solutions. Review and approve solution designs and vendor deliverables to confirm compliance with architectural standards. Evaluate emerging AI tools and vendors and perform build-versus-buy assessments with a preference for scalable owned capabilities. Establish and mature MLOps practices, including CI/CD, testing, model monitoring, drift detection, and retraining workflows. Develop real-time and near-real-time data products that support dashboards, alerts, and client-facing analytics. Implement responsible AI practices, including governance, bias evaluation, explainability, and regulatory compliance. Optimize cloud data and AI infrastructure for performance, reliability, and cost efficiency. Recruit, lead, and develop a cross-functional team of data engineers, ML engineers, data scientists, data architects, and BI developers. Partner with product and operations leaders to embed AI capabilities into frontline applications, IoT platforms, and client dashboards. Technologies: AI Architect Azure CI/CD Cloud IoT Support Kafka Machine Learning Python SQL Snowflake Spark HTTP LLM More: We are Nimbus Data Systems, a global company serving millions of guests each day across food and facilities in 15 countries. Our mission is rooted in service, and we are committed to helping our people, partners, communities, and planet thrive. We offer eligible employees comprehensive benefits, which may include medical, dental, vision, work/life resources, retirement savings options such as 401(k), and paid time off benefits like parental leave and disability coverage, subject to location and eligibility. This is a remote opportunity, and the posted compensation range is $150,000 to $160,000. We are an equal opportunity employer and consider qualified applicants in accordance with applicable fair chance and anti-discrimination laws. last updated 26 week of 2026