Software Architect, Sales & Success

Software ArchitectAutodesk is looking for a Software Architect to join our COO Architecture team, leading the architecture of next-generation Go-to-Market systems. In this role, you will report to the Distinguished Architect for Sales, Marketing, and Customer Success, and collaborate with a global team of architects driving Autodesk's digital transformation.You will play a key role in reimagining our GTM ecosystem by modernizing platforms and embedding AI-first and agent-driven architectures across Sales and Customer Success. This includes leveraging Agentic AI frameworks (e.g., Salesforce Agentforce) and integrating cutting-edge AI technologies such as OpenAI, Anthropic, and developer tooling like Cursor to automate workflows, enhance decision-making, and enable intelligent, autonomous business processes.This is a high-impact opportunity to shape Autodesk's revenue engine by designing scalable, secure, and intelligent systems that accelerate growth and operational efficiency.ResponsibilitiesLead end-to-end solution architecture and define the strategic roadmap for Sales and Customer Success platforms, with a strong focus on AI-driven automation and intelligent systemsArchitect agent-based and autonomous workflows using platforms like Salesforce Agentforce, enabling proactive customer engagement, pipeline acceleration, and operational efficiencyDesign and implement AI-powered GTM solutions, leveraging LLM ecosystems (OpenAI, Anthropic) for use cases such as:Intelligent lead scoring and routingSales copilots and customer success assistantsAutomated insights generation and forecastingConversational interfaces and workflow automationDefine scalable, event-driven and composable architectures, integrating CRM, CDP, ERP, and Customer Success platforms with modern data platformsStay at the forefront of innovation across:Generative AI, Agentic AI, and MLSalesforce ecosystem (Sales Cloud, Data Cloud, Einstein, Agentforce)Modern AI developer tooling (e.g., Cursor, prompt engineering frameworks)Drive adoption of AI-enabled architectures, ensuring responsible AI practices, governance, compliance, and data securityCollaborate cross-functionally with GTM, Product, Engineering, and Data teams to design AI-infused customer journeys and business processesDefine build vs buy strategies, including evaluation of AI platforms, open-source frameworks, and SaaS toolsArchitect and guide implementation of modern cloud-native, API-first, and data-centric platforms, enabling real-time intelligence and personalizationDevelop conceptual and logical data models in partnership with Data Architects, ensuring readiness for AI/ML workloadsTranslate complex technical and AI-driven concepts into clear strategies for both technical and non-technical stakeholdersEnsure non-functional requirements including scalability, reliability, security, compliance, and AI governance are metMinimum QualificationsBachelor's or Master's degree in Computer Science, Information Systems, or related technical field12+ years of experience delivering enterprise software solutions, with strong focus on Sales, Customer Success, and CRM domainsProven experience designing and delivering AI/ML or Generative AI solutions, including hands-on exposure to LLM platforms such as OpenAI, Anthropic, or similarExperience building or integrating agentic or autonomous systems, including exposure to Agentforce or similar agent frameworksSalesforce certifications and deep expertise across Sales Cloud, Data Cloud, and Customer Success ecosystemsStrong experience with data integrations and distributed systems (APIs, event-driven architectures, data pipelines, security layers)Domain knowledge across marketing, CRM, ERP, customer success platforms, and analytics ecosystems8+ years of experience working with customer success and sales systems, including business process mapping and customer journey designExperience architecting solutions for large-scale enterprises with a focus on scalability and resilienceFamiliarity with AI-assisted development tools (e.g., Cursor) and modern engineering practicesStrong understanding of compliance and data governance (GDPR, SOX, etc.), including implications for AI systems