Senior Forward-Deployed AI Engineer (Snowflake) - CONTRACT TO HIRE

Engg; United States; On-site; USD 180,000 - 250,000; Full time

Job summary

Abacus Insights is seeking a Senior Forward-Deployed AI Engineer to design and build AI/GenAI systems on Snowflake, delivering metrics and reporting from the semantic layer for diverse client engagements. This role blends hands-on implementation with technical leadership, often inside client environments, to shape the architecture and roadmap of AI components.

Initial focus on Snowflake semantic layer configuration and metrics delivery, with expansion into agentic AI work as the foundation

Qualifications

• 8+ years of software/AI engineering experience.
• Hands-on experience with Snowflake and related tooling.
• Experience delivering metrics and semantic layer-based solutions.

Responsibilities

• Design and build AI/GenAI systems on Snowflake for client environments.
• Define metrics requirements and deliver reporting from semantic layer.
• Lead technical vision and roadmap for AI components on Snowflake platform.
• Serve as senior AI technical voice on client engagements.
• Collaborate with product, data science, and operations teams to move AI efforts to production.

Skills

AI systems design

Technical leadership

Client-facing communication

Tools

Snowflake platform

Snowpark

Snowflake Cortex

Snowflake ML

SQL

Python

RAG tooling

Job description

About Us

Abacus Insights is transforming how data works for health plans. Our mission is simple: make healthcare data usable, so the people responsible for care and cost decisions can act faster, with confidence. We help health plans break down data silos to create a single, trusted data foundation. That foundation powers better decisions - so plans can improve outcomes, reduce waste, and deliver better experiences for members and providers alike. Backed by $100M from top investors, we’re tackling big challenges in an industry that’s ready for change. Our platform enables GenAI use cases by delivering clean, connected, and reliable healthcare data to support automation, prioritization, and decision workflows - and it’s why we are leading the way. Our innovation begins with people. We are bold, curious, and collaborative - because the best ideas come from working together. We embrace the thoughtful use of AI and automation to drive innovation and efficiency, and we look for individuals who are curious and adaptable - those excited to leverage emerging technologies to enhance how we work - while keeping human insight, connection, and our clients at the center of every decision. Ready to make an impact? Join us and let’s build the future together.

About the Role

This is a contract to hire position. The Senior Forward-Deployed AI Engineer is a senior individual contributor responsible for designing and building the AI and GenAI/agentic systems that power our platform on Snowflake, and for carrying that work directly into client environments. Hands-on Snowflake expertise is essential to this role. Databricks experience is a plus but not required. This is a forward-deployed role: the person in this seat spends a meaningful share of their time working inside client environments, not just building systems that clients eventually use. Candidates must bring prior, evidenced experience doing this kind of work already. The role’s focus will shift over time. Initially, the work is centered on configuring the Snowflake semantic layer and delivering metrics and reporting off of it for clients. As that foundation matures, the role expands into agentic AI work, which depends directly on the semantic layer already being correctly modeled and configured. On client engagements, this person is the senior-most AI technical voice, 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; someone else owns the engagement and its reporting, and this role does not have direct reports.

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 of the configured semantic layer
• Work directly 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 retrieval-augmented generation (RAG) systems, agentic workflows, and MCP-based tooling that draw on the semantic layer as their 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

• Serve as the senior-most AI technical voice on client engagements, helping shape technical direction and roadmap for AI components, without owning the engagement or its reporting
• Work directly with client stakeholders to scope AI/ML use cases, translate business requirements into technical solutions, and set realistic expectations on scope and timeline
• Implement and configure solutions within client environments, adapting the platform to client-specific data and constraints
• Serve as the technical point of contact for clients during implementation, including troubleshooting issues live with client teams
• Manage client relationships and expectations with the same rigor applied to the technical work itself

Cross-Functional Collaboration

• Partner with product, data science, and operations teams to move AI/ML work from prototype to production
• Communicate technical tradeoffs clearly to both technical and non-technical audiences, internal and client-facing
• Contribute to team best practices for AI engineering and client implementation work

What you bring to the team

• 8+ years of software/AI engineering experience, including hands-on design of AI/ML systems
• Deep, hands-on experience with Snowflake, including Snowpark, Snowflake Cortex, and Snowflake ML
• Hands-on experience building and maintaining semantic layers on Snowflake (e.g. Cortex Analyst semantic views), including modeling business logic and metrics for AI/agent consumption
• Experience delivering metrics and reporting off of a semantic layer for clients, including validating outputs against business logic
• Demonstrated experience designing and building GenAI/agentic systems: RAG, MCP-based tooling, agent orchestration patterns, and evaluation harnesses
• A proven track record workin