AI Product Engineer

We are transitioning our organization to an AI-first operational model. We are seeking an AI Product Engineer to architect and build the company’s central intelligence engine.

In this role, you will be the primary builder of automated intelligence systems—tools that not only retrieve insights but actively trigger workflows, and synthesize strategic intel across our entire business landscape.

This is a high-impact, hands-on engineering role requiring a convergence of three distinct skill sets:

• →

  Develop a unified intelligence layer that ingests signals from disparate sources (Product Telemetry, CRM, Call Transcripts, Marketing inputs) and processes them into actionable outputs.

• →

  Build robust integrations/webhooks to push AI-generated insights directly into workflow tools (e.g., pushing "Churn Risk" alerts into Salesforce

• Architect "Agentic" workflows where LLMs are granted permission to perform tasks 

• Implement advanced RAG to ground AI outputs in company documentation, historical data, and strategic context.

• Ensure rigorous evaluation and guardrails for non-deterministic models to prevent "hallucinations" in critical business workflows.

• Collaborate with Analytics Engineers to ensure the underlying data pipelines support real-time or near-real-time AI applications.

• Maintain security and privacy standards, ensuring that AI agents respect data access permissions across different departments.

• • Business Systems Knowledge: Experience working with APIs for major B2B tools (Salesforce, HubSpot, Zendesk, Jira, Marketo).

  • Workflow Automation: Experience with tools like Airflow, Zapier/Make (advanced usage), or custom workflow engines.

  • B2B Domain Expertise: Understanding of the interplay between Sales, Product, and Customer Success.

• The "Builder" Mindset: You are comfortable taking a high-level strategic requirement from leadership (e.g., "We need to automate lead qualification") and independently architecting and coding the solution.

• Systemic Thinking: You understand how a change in product data schema impacts the downstream marketing automation flow.

• Adaptability: You can switch contexts rapidly—from debugging a SQL query for Strategy to refining a prompt for Customer Support automation.