Description
Salesforce is the #1 AI CRM, where humans with agents drive customer success together. Here, ambition meets action. Tech meets trust. And innovation isn't a buzzword - it's a way of life. The world of work as we know it is changing and we're looking for Trailblazers who are passionate about bettering business and the world through AI, driving innovation, and keeping Salesforce's core values at the heart of it all. Ready to level-up your career at the company leading workforce transformation in the agentic era? Agentforce is the future of AI, and you are the future of Salesforce.
About the Spiff Team:
Spiff, a strategic part of the Salesforce Sales Cloud, is a leader in Incentive Compensation Management (ICM) software, combining intuitive design with a powerful processing engine to drive commissions automation at scale. Our mission is to provide customers with a trusted platform to increase visibility, supercharge selling, and unlock growth. This team is on the front lines of integrating a fast-growing, cloud-native application into the world's leading CRM platform.
The Role:
As a Software Engineering Architect focusing on Spiff, you will be the key technical leader defining and guiding the most critical architectural initiatives for Spiff's platform and services. Your work will directly ensure the massive scalability, seamless platform integration, and AI-driven efficiency of Spiff's compensation platform within the Salesforce ecosystem.
You will be expected to architect solutions across critical domains, from hyperscale infrastructure design and Hyperforce integration to advanced AI/ML systems for product intelligence.
Key Responsibilities:
I. Enterprise Scaling & Hyperscale Infrastructure Architecture
Define and lead the technical strategy for Enterprise Scaling across the Spiff platform to onboard extra-large customers and handle massive transactional volume, specifically focusing on Incentive Compensation Management (ICM) calculation performance.
Database Tier Scaling: Architect and implement advanced data strategies, including sharding, partitioning, and replication, to enable the database tier to scale horizontally and sustain the immense read/write throughput required by our largest customers.
Application Tier Scaling: Design the application architecture to be highly decoupled, elastic, and leverage cloud-native patterns on Hyperforce (Salesforce's public cloud architecture) for high-performance, low-latency service operation.
Establish system performance benchmarks and optimization roadmaps to consistently achieve industry-leading processing speed for complex compensation plan calculations.
II. Core Platform Integration and Adoption
Partner with Salesforce Core Engineering teams to strategically embed Spiff functionality into core and near-core Salesforce components (e.g., Sales Cloud, CRM platform APIs).
Define the architecture and protocols necessary to enable easier adoption for existing and new customers by making Spiff's features natively accessible within the Salesforce user experience and data model.
Design secure, high-throughput integration patterns (APIs, events, data synchronization) between Spiff’s services and the Salesforce platform, ensuring data consistency and adherence to Salesforce security standards.
III. GenAI and ML Architecture for Proactive Insights
Use GenAI and ML architecture to enable proactive insights with respect to sales incentives for customers, such as predicting commission payouts, identifying sales goal misalignment, and recommending optimal compensation plan adjustments.
Integrate Spiff's intelligent services with existing agents in the Salesforce Agentic Framework, ensuring the smooth flow of incentive data and calculated commission results to power CRM workflows and user-facing AI assistants.
Architect and contribute to the GenAI research team to achieve consistently accurate results by implementing sophisticated data augmentation techniques, including Knowledge Graphs, Retrieval-Augmented Generation (RAG), and Vector Databases, to enhance data context and drive model performance.
Key Accomplishments (Success will be measured by):
Successfully architecting the platform to support 5x the current data and transaction volume for new Enterprise customers.
Designing and overseeing the technical embedding of Spiff into core Salesforce products, resulting in a measurable increase in new customer adoption.
Delivering a production-ready GenAI/ML architecture that provides measurable proactive incentives insights and is fully integrated into the Salesforce Agentic Framework.
Minimum Qualifications:
10+ years of experience in software engineering, with at least 3 years as a Software Engineering Architect for large-scale SaaS platforms.
Demonstrated success architecting multi-tenant platforms for massive scale (1M+ users/transactions per day) at both the application and database tiers.
Proven ability to design and implement robust, highly available microservices and distributed systems.
Extensive experience with the full lifecycle of production-grade AI/ML model deployment and MLOps.
A related technical degree required.
Preferred Qualifications:
Direct experience with Salesforce architecture, Sales Cloud, or Hyperforce infrastructure.
Expertise in Ruby on Rails, Elixir and related technologies.
Experience supporting large scale applications in production environments.
Demonstrated ability to lead technical strategy across multiple highly technical engineering teams.
For roles in San Francisco and Los Angeles: Pursuant to the San Francisco Fair Chance Ordinance and the Los Angeles Fair Chance Initiative for Hiring, Salesforce will consider for employment qualified applicants with arrest and conviction records.