Technical Product Intern

    Elloe AI | Immune System for AI logo

    Elloe AI | Immune System for AI

    11-50 employeesAustin, TexasTechnology, Information and Internet
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    Best applied by Sep 24

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    About the role#

    This role is for a technical product thinker who wants to define how trust works in AI systems. You will prototype safety overlays, translate policy into product logic, and map the competitive edge of our infrastructure. You will work with engineers, safety leads, and the go-to-market team to ensure our products scale with clarity.

    What you'll do#

    • Design and wireframe user-facing safety elements like audit overlays, policy badges, and drift alerts.
    • Build demo views and product mockups for partners and buyers.
    • Analyze the features and positioning of tools such as Vanta, CalypsoAI, and Credo.
    • Shape our differentiation regarding real-time enforcement versus passive monitoring.
    • Translate compliance frameworks like the AI Act, HIPAA, and SOC2 into traceable product logic.
    • Collaborate with the GTM team to express enforcement clarity through product demos and case studies.

    What you'll need#

    • You are a technical student, preferably in Computer Science, Electrical Engineering, or product design.
    • You are comfortable spec-ing flows or wireframing interfaces.
    • You have a curiosity about compliance, explainability, and high-trust systems.
    • Experience with LLM workflows, LangChain, or infrastructure stacks is a plus.

    Location & details#

    • Term: Fall 2026.
    • Duration: 10 to 12 weeks.
    • Modality: Remote, with a preference for timezone overlap with the EU or the US East Coast.
    • Employment: Full-time.
    • Compensation: Paid via a competitive stipend.

    About Elloe AI | Immune System for AI

    Elloe AI operates as a compliance layer for artificial intelligence. It provides safety tools for generative models used in regulated sectors like hospitals and government agencies. The company focuses on tracing and flagging model outputs to prevent errors. It is based in Austin, Texas, and maintains a staff of 11 to 50 employees.

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