Senior Group Software Development Manager, Generative AI

Job Requisition ID #

26WD96393

Position Overview

Autodesk is transforming the architecture, engineering, and construction industries by building cloud-scale software, data platforms, and AI-enabled capabilities that help customers design, build, and operate the world around them. As a Senior Software Development Manager, you will lead multiple engineering managers and their teams to deliver robust APIs, model-control platforms, scalable data pipelines, and services that power modern agentic experiences. You will translate product priorities into technical direction, grow leaders and engineers, and champion ways to increase engineering throughput by adopting AI and automation across the development lifecycle.

Responsibilities

• Technical & strategic leadership. Set and communicate the engineering strategy and technical roadmap for the organization. Lead architecture decisions for scalable, secure systems and ensure design tradeoffs align to business goals
• Manager-of-managers role. Hire, mentor, and develop engineering managers; ensure clear career frameworks, performance calibration, and manager effectiveness. Build a culture of ownership, psychological safety, and continuous improvement
• Deliver predictable results. Break large, ambiguous initiatives into time-bound milestones. Drive cross-team delivery, manage risk and dependencies, and ensure teams ship high-quality work on schedule
• Increase engineering productivity with AI & automation. Champion and operationalize AI-driven tooling (e.g., code generation, automated tests, intelligent code review, documentation generation, developer assistants, CI automation) to reduce manual work and increase developer throughput. Set measurable productivity targets and lead adoption across teams
• API-first strategy for agentic experiences. Define and own an API and SDK strategy that supports agentic workflows: action APIs, capability discovery, connector patterns, tool invocation contracts, long-running asynchronous flows, event-driven orchestration, idempotency and transactional semantics, and clear versioning and compatibility guarantees
• Platform and reuse. Identify and consolidate common capabilities into shared platform services to remove duplication and accelerate product teams
• Operational excellence. Own SRE practices for services in your domain: monitoring, alerting, incident response, capacity planning, and cost management
• Cross-functional partnership. Work closely with Product, ML/Research, UX, Security, and Cloud Platform to align roadmaps, scope features appropriately, and deliver integrated solutions
• Talent & hiring. Build a strong bench of engineering managers and senior engineers; run hiring programs, interview calibration, and onboarding improvements

• 10+ years of professional software engineering experience shipping production services
• 3+ years of people management experience
• Demonstrated leadership of teams that build API-first platforms, event-driven systems, and/or large-scale data platforms
• Practical experience with model serving and orchestration, or with platforms that manage long-running, stateful distributed workflows
• Experience designing and shipping SDKs, connectors, and integration patterns for external systems
• Strong track record of recruiting, mentoring, and growing engineering managers and/or senior technical talent
• Practical experience with cloud-native technologies (containers/Kubernetes, microservices), streaming and batch data systems, and API design
• Excellent communication skills and experience influencing cross-functional stakeholders

• Experience building agentic or autonomous systems, orchestration frameworks, or production model-control platforms (MCPs)
• Experience in AEC or adjacent design/engineering domains (familiarity with CAD/BIM, or construction workflows) is helpful
• Direct experience with ML/AI infrastructure, model serving, or deploying foundation models in production
• Experience driving adoption of developer productivity tooling and automation at scale
• Familiarity with multi-modal inputs, long-running asynchronous workflows, and event-driven/actor architectures
• Familiarity with security, privacy, and compliance considerations for customer data and model-driven systems