AI Engineer

Role Overview 

We’re hiring an AI Engineer to build and scale our internal AI tooling and workflows. You’ll create the foundational systems—skills, tooling, and infrastructure—that enable teams to use LLMs effectively in their day-to-day work. 

This role sits within the Accounting organization and focuses on improving finance and accounting workflows through applied AI. You’ll work closely with stakeholders to identify high-impact use cases and translate them into reliable, production-ready systems. 

This is a growing team, and you’ll play a key role in shaping how AI is applied in practice—from defining core abstractions to establishing best practices for evaluation, reliability, and composability. 

This is not a traditional ML role. The focus is on applied AI—building reliable, composable systems using tools like Claude and Cursor, and making those capabilities accessible to non-technical users. 

Core Responsibilities 

• Build internal AI skills and tooling. Design and implement modular skills in Cursor, Claude, and related tools that connect to core systems such as Snowflake, Google Drive, and Slack. Create clean abstractions that let non-technical users compose these primitives into useful workflows without writing code. 

• Own the AI development environment. Establish and maintain the infrastructure the team uses to build with AI tools, including Claude Code, Cursor, and emerging tools. Create templates, patterns, and documentation that help the team ship faster. 

• Design for composability. Think deeply about the interfaces between AI components. Build systems where outputs from one tool become inputs to another, enabling complex capabilities from simple, well-designed primitives. 

• Build reliable AI systems. Define and implement evaluation frameworks, unit tests, and guardrails to ensure AI outputs are accurate, safe, and consistent. Develop automated test suites, monitoring, and feedback loops that catch regressions, enforce quality standards, and make model behavior observable and debuggable. 

Technical Skills & Requirements 

• Strong programming skills in Python and/or TypeScript, with experience building and shipping production-grade systems. 

• Hands-on experience working with LLMs and modern AI tooling, including prompt engineering, tool use, and multi-step workflow orchestration. 

• Experience designing and implementing AI-powered systems that integrate with external and internal APIs such as Snowflake, Google Drive, and Slack. 

• Proficiency in building modular, composable AI components such as skills, agents, and tools that can be reused and combined into larger workflows. 

• Experience with evaluation and testing of AI systems, including unit testing, eval frameworks, regression testing, and guardrails for safety, reliability, and correctness. 

• Familiarity with techniques for controlling and improving model behavior, including structured outputs, function calling, retrieval-augmented generation, and prompt/version management. 

• Strong understanding of system design, including data flow between AI components, observability, debugging, and performance considerations. 

• Experience setting up AI development workflows and environments, including prompt iteration, experimentation tooling, and CI/CD for AI systems. 

• Ability to translate ambiguous problems into practical AI solutions, with strong product intuition, especially when designing for non-technical users. 

 

We are committed to providing and promoting Equal Employment Opportunity and Affirmative Action to all employees and applicants following all local, state, and federal laws and regulations governing personnel activities. It is our policy to provide and promote equal & affirmative employment opportunity to all employees and applicants following all local, state, and federal laws and regulations governing personnel activities.