Who you are

• You’ll need hands-on technical experience with modern ML/AI stacks and data platforms, plus demonstrated success hiring, coaching and delivering large cross-functional programs in a matrix environment
• 8+ years of relevant experience in software engineering, data engineering, machine learning or analytics, with 3+ years of people-management experience (or equivalent leadership experience) in a matrix environment
• Senior manager/manager level experience with end-to-end ownership is expected
• Proven track record building and shipping production ML/AI systems as well as operating data/analytics platforms at scale. Experience integrating third-party models and building custom model components
• Strong technical fluency across: Python, ML frameworks (PyTorch/TensorFlow), ML lifecycle tools (MLOps, model CI/CD), cloud platforms (AWS preferred), containerization (Docker/Kubernetes), and data engineering (SQL, ETL pipelines, dbt or similar)
• Demonstrated experience with analytics tooling and visualization platforms (Looker, Tableau) and building robust reporting/observability pipelines
• Hands-on experience defining data models, instrumenting metrics, and delivering dashboards and product analytics to influence product and GTM decisions
• Excellent cross-functional communication and stakeholder management skills; ability to translate technical tradeoffs into business outcomes
• Strong bias for operational rigor: testing, monitoring, data quality and reproducibility for analytics and ML systems
• Bachelor’s degree in Computer Science, Engineering, Statistics, or equivalent experience. Advanced degree a plus
• Prior experience in design / manufacturing / AEC industries
• Familiarity with C++ / TypeScript / front-end stacks (helpful where product integrations require full-stack coordination)
• Experience with product experimentation (A/B testing), feature flagging, and product analytics instrumentation
• Prior experience structuring combined Applied AI + Analytics organizations or hiring across these disciplines
• A builder who hires and develops great engineers and analysts; hands-on where it matters but able to scale through others
• Comfortable operating in a fast-moving, collaborative, matrixed organization; able to set strategy while being pragmatic about delivery
• Passion for turning data and models into real product value - measurable improvements in customer outcomes and business KPIs

What the job involves

• We’re looking for an experienced engineering leader to build, scale and operate a combined Applied AI and Analytics organization that delivers production-grade AI features and world-class analytics across Autodesk products
• You will lead a cross-functional team of engineers (Applied AI and Analytics), own roadmap execution and quality of delivery, and partner closely with Product, Engineering, Design, and GTM teams to turn data and ML investments into measurable product and business outcomes
• This role sits at the intersection of product, data and engineering
• The team will be charged with producing both applied ML solutions (leveraging off-the-shelf and custom models integrated into our product stack) and analytics infrastructure (ETL, observability, dashboards and KPI reporting)
• In this exciting position, you’ll lead a team at the forefront of our product AI and analytics efforts - combining modern ML with production engineering and data science to deliver customer impact. You’ll work with cross-functional teams across product, engineering and business leaders to bring measurable outcomes to market
• Lead and grow a high-performing Applied AI & Analytics team (6 - 10 direct reports comprised of Applied AI engineers and Analytics engineers). Hire, mentor, calibrate performance and build career paths
• Define and execute the technical strategy and roadmap for applied AI capabilities and analytics capabilities that align to product and business goals
• Deliver production-grade AI/ML features by combining off-the-shelf models and custom components and integrating them into our product stack and CI/CD/MLOps pipelines
• Build and own analytics platforms: data ingestion/ETL, modelling, observability, reporting, and dashboards to surface product and business insights. Ensure quality and standardization across reporting
• Drive operational excellence: implement robust MLOps practices, testing, monitoring, rollout (A/B experiments, feature flags), and production observability for both models and data pipelines
• Partner closely with Product Management, UX, Platform and Engineering teams to scope work, prioritize outcomes, and ensure timely delivery. Serve as the technical & people leader to influence product decisions and tradeoffs
• Translate business needs into scalable data and AI solutions; define success metrics, KPIs and SLAs and report results to leadership
• Establish best practices for model governance, data quality, instrumentation, and reproducible analytics workflows
• Represent the team with stakeholders and executive reviews, present findings and recommendations clearly and persuasively