Software Engineering Architect, Salesforce

• 15+ years of hands-on software development experience with a proven track record of designing, building, and delivering large-scale, high-performance distributed systems
• A related technical degree is required
• Extensive cloud infrastructure architecting & development experience (FinOps, cost optimization, capacity planning, or data platforms)
• Extensive experience working in the public cloud (AWS, GCP, Azure)
• Deep expertise in big data platforms (Trino/Presto, Iceberg, Airflow, Spark)
• Knowledge of AI/ML systems, LLM optimization, or agentic workflows
• Love getting things done (e.g. hands-on prototyping a new approach)
• Experience building products used by 1000+ internal users

Desirable

• CECM (Cloud Economics & Capacity Management) develops intelligent, data-driven tools which enable strategic financial operations (FinOps) decision-making pertaining to Salesforce infrastructure expenditure and capacity management
• We are building a platform that provides near real-time monitoring of Cloud and AI cost and capacity utilization of the infrastructure, which will help in optimizing resource allocation, forecasting spend, and minimizing costs
• We incorporate advanced machine learning techniques to turn the petabytes of data generated by our global infrastructure into actionable predictions and business insights used by FinOps practitioners, internal service owners, and technical leaders daily
• As an internal tooling team, engineers are expected to directly interact with customers to develop requirements and design, release and maintain distributed systems with visibility throughout Salesforce
• We are looking for a technical ace and thought leader in cloud economics, data platforms, and infrastructure optimization to join the team
• This is a fantastic opportunity for someone who is passionate about building scalable, resilient, distributed systems that collect, process, and analyze massive volumes of cloud cost and usage data
• We embrace AI not just to improve our productivity but also to empower our users to access our capabilities towards a Headless experience
• Design and implement architectural solutions for the CECM platform, ensuring enterprise-grade scalability, reliability, performance, maintainability, and security
• Lead the architectural design of complex distributed systems
• Establish and champion technical standards, overarching architectural principles, frameworks, and best practices for the CECM platform, driving continuous improvement and innovation
• Collaborate extensively with cross-functional teams and act as a critical liaison across the broader engineering organization to ensure seamless integration with other platform services and drive technical alignment
• Mentor and provide technical guidance to engineers and data scientists, fostering their technical development and contributing to high-level technical discussions to cultivate a culture of engineering excellence
• Evaluate, research, and introduce new technologies and architectural patterns, leading prototyping efforts to shape the future evolution of the CECM platform architecture
• Define and track key technical metrics for platform health and performance, applying deep expertise to resolve complex real-time challenges and ensure highly available services
• Some Current Areas of Focus:
• How can we ensure we provide highly compelling, "first class" cost optimization and capacity management offerings (e.g. easy to use, highly enabling, and well integrated with Salesforce's centralized infrastructure / tooling)?
• How can we efficiently and effectively support our cost analytics and forecasting infrastructure within and across the major cloud providers (AWS, GCP, Azure, 1P)?
• How can we strike the right balance of isolation and cost efficiency for the hundreds of teams and thousands of users that leverage our data analytics platform?
• How should we weave in AI agents to ease and accelerate platform usage and support, achieving 75%+ autonomous success rates?
• How can we architect TOIN (Token Optimization Index) to manage Salesforce's AI/LLM spend with the same rigor as our infrastructure cost optimization?
• How do we achieve 99% forecast accuracy while supporting rapid scaling of Data Cloud, Agentforce, and C360?
• How should we architect for multi-cloud by default: cost visibility, reservation management, forecasting without duplicating infrastructure?
• How can we ensure we serve as the de facto destination for infrastructure analytics and a turnkey platform for cost-conscious engineering