Principal Software Engineer, AI

Salesloft, in partnership with Clari, is focused on revolutionizing enterprise revenue through AI-driven solutions. The Principal Software Engineer, AI will lead the design and development of the AI Context Layer, ensuring that AI agents have access to high-quality data for informed decision-making.

Responsibilities:

• Embed with feature teams across the organization to understand what they need from the context layer - what data, at what quality, in what form - and use those insights to drive the platform roadmap
• Build the technical vision and roadmap for our Context Layer: a collection of high-quality data products - including a knowledge graph, RAG engines, and retrieval/search infrastructure - that give AI agents access to the best possible context about our customers and their revenue processes
• Design and own the access control and RBAC model for the context layer - a genuinely hard problem at the intersection of multi-tenant data, agent identity, and fine-grained permissions
• Define and evolve the APIs, SDKs, and developer interfaces that teams use to interact with the context layer, ensuring they are ergonomic, well-documented, and built for scale
• Identify data platform dependencies and work closely with data engineering to ensure the underlying data infrastructure can reliably service the context layer's needs
• Drive architecture discussions, design and code reviews, and set the technical standard for how context is modeled, stored, retrieved, and governed
• Address governance and security requirements around data access, lineage, and auditability in an AI context
• Contribute to hiring strong and diverse talent to strengthen the team
• Contribute actively to internal documentation, onboarding, and platform adoption programs to ensure the Context Layer is well-understood and widely used

Requirements:

• 12+ years of professional software engineering experience, with a strong focus on data-layer or search/retrieval infrastructure
• Proven experience designing and building knowledge graphs and/or large-scale retrieval and search systems in production
• 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-rich environments, with the judgment to navigate the tradeoffs involved
• Experience designing developer-facing APIs and SDKs, with a track record of building interfaces that are intuitive and well-adopted internally
• Familiarity with data governance, lineage, and audit-ability requirements - particularly in enterprise or regulated contexts
• Demonstrated ability to lead technical direction across multiple teams and drive complex, multi-stakeholder projects to delivery
• Experience with Python and/or Java; comfort working across data engineering, backend systems, and platform infrastructure
• Excellent communication skills - able to work across engineering, product, data, and leadership to align on direction and drive outcomes