• Own all four adoption phases end-to-end for a portfolio of enterprise accounts, from first post-deployment kickoff through renewal signature. • Maintain a customer-specific 30/60/90 roadmap, updated weekly and reviewed in every customer sync. • Run every customer-facing meeting type in the process: kickoffs, team enablement sessions, bi-weekly product feedback calls, power-user 1:1s, weekly syncs, exec/leadership syncs, and Quarterly Business Reviews. • Publish a monthly async leadership update to each account’s executive sponsors — written, concise, and built on real usage data. • Own customer-specific integrations, custom prompt engineering, and edge-case debugging for each assigned account. • Instrument and maintain accuracy tracking in collaboration with the customer — ensuring the dataset is customer-owned and credible, not vendor self-reported. • Identify and capture failure modes through power-user 1:1s, then work with the product team to translate them into roadmap items. • Debug and resolve platform issues surfaced during adoption, coordinating with engineering when needed.

• Own all four adoption phases end-to-end for a portfolio of enterprise accounts • Maintain a customer-specific 30/60/90 roadmap, updated weekly • Run every customer-facing meeting type in the process • Publish a monthly async leadership update to each account’s executive sponsors • Own customer-specific integrations, custom prompt engineering, and edge-case debugging for each assigned account. • Instrument and maintain accuracy tracking in collaboration with the customer • Identify and capture failure modes through power-user 1:1s • Debug and resolve platform issues surfaced during adoption • Synthesize customer feedback into structured product roadmap input

• Design and deliver distributed architectures for large-scale, cloud-based enterprise systems (AWS, Azure, GCP). • Integrate Agentic AI capabilities into enterprise software. • Act as a technical authority, setting standards for security, scalability, and performance, ensuring poor code or weak architecture is prevented from entering production. • Translate vague customer requirements into actionable technical designs. • Lead discussions, challenge ideas, and align teams on a clear technical direction. • Collaborate with engineers and stakeholders to ensure timely delivery of MVPs and production-ready solutions. • Design and develop robust back-end services using Node.js, Python, or other back-end technologies. • Integrate large language models (LLMs) and multimodal AI models into applications. • Optimize application performance, ensuring efficiency in AI inference and API response times. • Ensure security, scalability, and compliance of AI-driven applications. • Stay up to date with the latest advancements in Generative/Agentic AI, web development, and cloud technologies.

• Write production-quality code, design scalable platform capabilities, and set the technical standard for how the team builds. • Deliver reusable platform capabilities such as unlocked packages, shared Apex and LWC libraries, custom metadata frameworks, and CPQ configuration patterns that reduce duplication, enforce consistency, and accelerate team velocity. • Design scalable solutions using Salesforce DX, platform events, custom metadata types, and cloud-specific best practices. • Develop and maintain integration systems and tooling outside of Salesforce, including REST and SOAP APIs, MuleSoft, and ETL tools. • Build services and automation in Python or another object-oriented language where it is the right tool for the job. • Conduct architecture reviews, solution design sessions, and code reviews for complex implementations across Apex, LWC, Flow, and CPQ. • Build and maintain CI/CD pipelines using Salesforce DX, Gearset, GitHub, and other industry-standard tools. • Mentor and coach engineers across teams on Salesforce development and engineering best practices.