Senior Forward-Deployed AI Engineer (Snowflake)
Abacusinsights · United States
About this role
## Senior Forward-Deployed AI Engineer (Snowflake) ### About Abacus Insights Abacus Insights is transforming how data works for health plans—making healthcare data usable so care and cost decision-makers can act faster, with confidence. We help health plans break down data silos to create a single, trusted data foundation that powers better decisions, improves outcomes, reduces waste, and delivers better experiences for members and providers. Backed by $100M from top investors, we’re building a platform that enables GenAI use cases by delivering clean, connected, and reliable healthcare data for automation, prioritization, and decision workflows. ### About the Role The **Sr. Forward-Deployed AI Engineer** is a senior individual contributor responsible for designing and building AI and GenAI/agentic systems that power our platform on **Snowflake**, and for carrying that work directly into **client environments**. This is a **forward-deployed** role—meaning you’ll spend a meaningful share of your time working inside client environments (not just building systems clients later use). Candidates must bring prior, evidenced experience doing this kind of work already. The work starts with configuring the **Snowflake semantic layer** and delivering **metrics and reporting** off of it. As the foundation matures, the role expands into **agentic AI work** that depends on the semantic layer being correctly modeled and configured. You’ll serve as the **senior-most AI technical voice** on client engagements—trusted to work through ambiguous problems and help shape the technical vision and roadmap for AI components. This is **technical leadership**, not engagement ownership or people management. ### Your Day to Day **Semantic Layer & Metrics Reporting (initial focus)** - Design, configure, and maintain the Snowflake semantic layer (e.g., Cortex Analyst semantic views), modeling business logic and metrics definitions accurately against client requirements - Build and deliver metrics and reporting for clients off the configured semantic layer - Work with client stakeholders to define metrics requirements, validate outputs against business logic, and resolve discrepancies - Write efficient, production-grade **SQL and Python** to support semantic layer configuration, metrics pipelines, and reporting delivery **GenAI & Agentic Systems (as the role evolves)** - Design and implement **RAG** systems, agentic workflows, and **MCP-based tooling** that use the semantic layer as the source of truth - Build and maintain evaluation harnesses to test and monitor AI/agent quality and performance - Apply sound judgment on model selection, prompting strategy, and system design tradeoffs - Own technical architecture and model strategy decisions for AI systems built on the Snowflake platform **Client-Facing / Forward Deployed Engineering** - Act as the senior AI technical voice on client engagements (without owning the engagement or its reporting) - Scope AI/ML use cases with stakeholders, translate business requirements into technical solutions, and set realistic expectations on scope and timeline - Implement and configure solutions within client environments, adapting to client-specific data and constraints - Troubleshoot issues live with client teams during implementation - Manage client relationships and expectations with the same rigor as the technical work **Cross-Functional Collaboration** - Partner with product, data science, and operations to move AI/M
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