Principal Software Engineer, AI

Salesloft is building the next era of enterprise revenue powered by AI. The Principal Software Engineer, AI will be responsible for designing and building the AI Context Layer, ensuring that AI agents have access to high-quality data about revenue processes.

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