Software Engineer, AI

About the Company

Clari + Salesloft are working together to shape the future of enterprise revenue management through AI-powered insights and predictive decision-making. By combining their platforms, data and AI capabilities, the companies are building a Predictive Revenue System that helps teams and AI agents work together to make better decisions and support consistent business growth.

Their platforms serve thousands of customers and provide insights into how revenue is generated, including the activities, timing and outcomes that influence sales performance. The Engineering Team focuses on building a secure, enterprise-grade revenue intelligence platform that supports critical business processes.

About the Role

Clari + Salesloft is seeking a Principal Software Engineer, AI to lead the design and development of its AI Context Layer. This platform will provide AI agents with high-quality, reliable and well-governed information about customers and their revenue processes.

The role combines technical architecture, AI retrieval infrastructure, data governance and cross-functional engineering leadership. The Principal Engineer will define the platform’s technical direction, work closely with feature teams and data engineering, and build scalable systems that make contextual data accessible, secure and useful across enterprise applications.

Key Responsibilities

• Work closely with feature teams across the organization to understand their context-layer requirements, including data availability, quality and format, and use those needs to guide the platform roadmap.
• Define the technical vision and roadmap for the Context Layer, including knowledge graphs, retrieval-augmented generation (RAG) engines, and search and retrieval infrastructure.
• Design and develop data products that give AI agents access to relevant, high-quality information about customers and their revenue processes.
• Design and own access control and role-based access control (RBAC) models for multi-tenant environments, accounting for agent identity, data permissions and security requirements.
• Define and evolve APIs, SDKs and developer interfaces that enable engineering teams to use the Context Layer effectively, with an emphasis on usability, documentation and scalability.
• Identify dependencies across the data platform and collaborate with data engineering teams to ensure the underlying infrastructure reliably supports context-layer requirements.
• Lead architecture discussions, design reviews and code reviews, establishing technical standards for how contextual data is modeled, stored, retrieved and governed.
• Address enterprise data governance and security requirements, including access management, data lineage and auditability.
• Provide cross-team technical leadership, connect platform domains and align engineering decisions with broader organizational priorities.
• Drive complex, multi-stakeholder technical initiatives from planning through delivery.
• Contribute to hiring strong and diverse engineering talent.
• Support internal documentation, onboarding and platform adoption initiatives to help teams understand and use the Context Layer effectively.

Required Qualifications

• 12+ years of professional software engineering experience, with a strong focus on data-layer systems or search and retrieval infrastructure.
• Proven experience designing and building production-grade knowledge graphs and/or large-scale search and retrieval systems.
• Deep expertise in RAG architectures, vector databases and embedding-based retrieval, including evaluation, quality tuning and relevance optimization.
• Strong understanding of access control and RBAC design in multi-tenant, data-intensive environments, with the ability to evaluate and manage related technical trade-offs.
• Experience designing developer-facing APIs and SDKs, with a record of creating intuitive interfaces that gain adoption across engineering teams.
• Familiarity with data governance, lineage and auditability requirements, particularly in enterprise or regulated environments.
• Demonstrated ability to guide technical direction across multiple teams and deliver complex projects involving multiple stakeholders.
• Experience with Python and/or Java, along with the ability to work across data engineering, backend systems and platform infrastructure.
• Excellent communication skills and the ability to collaborate with engineering, product, data and leadership teams to …