AI Product Engineer

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Skills you'll use

What you'll do

• 1. Building the "Enterprise Brain" (Architecture & Integration)
• 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
• 2. AI Logic & Agent Implementation
• 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.
• 3. Data Engineering & Governance
• 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.

Who can apply

• Minimum Qualifications:
• Education: Bachelor’s degree in Computer Science, Engineering, or equivalent practical experience.
• Software Engineering: 3+ years of experience in Python development, with strong proficiency in API development (FastAPI/Django) and building integrations between SaaS platforms.
• AI/ML Application: Proven experience building applications using LLM APIs and orchestration frameworks, Experience with "Agent" concepts.
• Data Proficiency: Strong SQL skills and familiarity with cloud data warehouses (Snowflake/BigQuery).

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