Principal AI Platform Engineer, Applied AI

In this Principal Engineer role, you lead the design and expansion of Firn—the company-wide data and AI platform—focusing on GTM intelligence, agents, and tools. You’ll unify and modernize existing GTM services onto Firn, build production-grade platform services, and establish robust governance, observability, and learning loops. You’ll balance internal customer needs with scalable architecture, making decisions on what to build, buy, or retire. This role offers strategic impact across Marketing, Sales, and Partnerships as the platform scales.

• Meaningful equity stake
• Competitive base salary
• Flexible working
• Generous PTO
• Private medical insurance
• Company pension

• Design and own the GTM intelligence engine on Firn, including data and AI that decide who to engage and how, with learnings from outcomes
• Ship and standardize Agents and tools on the factory framework with evaluation steps for trust and inspectability
• Shape the platform architecture (MCP gateway, LLM gateway, tracing, ledger) and guide growth to support more of the company’s work
• Ensure production-grade quality: version control, CI, alerting, recovery, cost visibility, documentation, and smooth handover for services
• Implement logic as code by moving rules from individual tools into versioned platform code and exposing them as endpoints
• Establish learning loops that tie platform actions to outcomes, enabling continuous improvement
• Own evaluation and tracing infrastructure used by engineers for production-grade checks
• Set and communicate the engineering bar and platform roadmap for the Applied AI team
• Balance build vs buy decisions, and determine ownership and handover of services to teams
• Work with internal customers (growth, sales, marketing) to translate requirements into platform designs
• Demonstrate an AI-native approach through a workflow, agent, or tool you built and still use

• Extensive production software experience
• Experience designing, shipping, and running systems relied upon by other teams
• Proficiency in Python or TypeScript with SQL, CI/CD and cloud infrastructure
• Built LLM-based systems with agents, MCP servers, gateways, tracing and evaluation; understanding production failure modes
• Platform-level instincts and ability to distinguish what should be deterministic code vs. agent decisions
• Data platform fluency with Snowflake or equivalent warehouse, dbt, data contracts, data movement pipelines
• Operational discipline including alerting, recovery, runbooks, cost tracking
• Ability to articulate and justify where an agent belongs and where human judgment is required
• Demonstrable AI-native working style and prior work sample to discuss in interview
• Comfort collaborating with non-engineers (growth, sales, marketing) to shape requirements
• Technical direction experience without formal title and influence over a platform’s design

• Collaborative stakeholder management
• Clear communication with non-engineers
• Strategic judgment on platform boundaries
• Python
• TypeScript
• SQL