AI Implementation Specialist (AI Governance, Gateways, Platform Control)

Island Technology Inc

  • Dallas, TX
  • 6 days ago

    Highlights

    In this role, you will serve as a trusted advisor on AI strategy, guide large-scale enterprise AI rollouts, and configure critical AI control points, such as MCP Gateways and custom hooks, to protect. Practical experience configuring and deploying AI integration layers, LLM Gateways, or API control points (e.g., Model Context Protocol/MCP, LiteLLM, LangChain, or.

    Numbers & Facts

    LocationDallas, TX

    Description

    About The Role

    Island is seeking an AI Implementation Specialist to help enterprise customers design,

    deploy, and operationalize AI governance and control across their organizations. In this role,

    you will serve as a trusted advisor on AI strategy, guide large-scale enterprise AI rollouts,

    and configure critical AI control points, such as MCP Gateways and custom hooks, to protect

    sensitive data and enforce compliance. You will lead technical discovery, deliver executive-

    level platform demonstrations, and architect scalable solutions using Island's Enterprise AI

    Platform.

    Key Responsibilities

    1. Collaborate with customers to gather process and AI strategy requirements, clarify

    objectives, define success metrics, and align priorities with Island's AI Platform

    capabilities.

    1. Provide consultative guidance to customers on AI security, governance, visibility, and

    operationalization best practices, using telemetry to recommend policies that keep

    them compliant with organizational and regulatory standards.

    1. Design and implement AI governance policies integrated with customer

    infrastructure, delivering visibility and control across SaaS and desktop AI

    applications and agents.

    1. Deliver executive-facing technical demonstrations of Island's AI Platform, tailored to

    the customer's industry and use cases.

    1. Create documentation, deliver technical enablement sessions, and train customers on

    Island's AI platform.

    1. Troubleshoot, maintain, and optimize existing AI deliverables in customer

    environments.

    1. Engage with customer stakeholders across technical and business teams to ensure

    successful deployment and adoption of AI solutions.

    Requirements

    1. 2+ years in a customer-facing technical role (e.g., Solutions Architect,

    Implementation Engineer, Sales Engineer, Technical Account Manager) at an

    enterprise SaaS, Cybersecurity, or Cloud infrastructure vendor.

    1. 2+ years of enterprise software delivery or technical consulting experience, with

    hands-on exposure deploying AI tooling, LLM integrations, or modern API

    architectures.

    1. Proven track record of guiding Fortune 500 or large enterprise clients through

    complex technical deployments or digital transformation initiatives.

    1. Strong working knowledge of enterprise security concepts, Data Loss Prevention

    (DLP), Zero Trust concepts, and how LLMs handle sensitive data (PII, IP, source

    code).

    1. Hands-on experience integrating and managing AI control points (e.g., LLM

    Gateways, API proxies, inference hooks, or Model Context Protocol connectors).

    1. Strong understanding of web application execution, API integration models, and

    event-driven architectures (REST, Webhooks, JSON-RPC, JavaScript/browser

    execution models).

    1. Strong executive communication skills, with a demonstrated ability to translate

    complex technical architectures for C-level, security, and business stakeholders.

    1. Creative problem-solving skills with a track record of driving successful customer

    outcomes in fast-paced, ambiguous environments.

    Preferred Qualifications

    1. Bachelor's degree in Computer Science, Cybersecurity, Information Systems, or

    equivalent practical experience. Relevant industry certifications (e.g., CISSP, CCSP,

    or Cloud/AI Practitioner certifications) are a plus.

    1. Practical experience configuring and deploying AI integration layers, LLM Gateways,

    or API control points (e.g., Model Context Protocol/MCP, LiteLLM, LangChain, or

    custom inference hooks).

    1. Familiarity with enterprise Zero Trust architectures, Enterprise Browsers, or endpoint

    security platforms.

    1. Experience integrating platform telemetry and audit logs with enterprise SIEM or

    analytics platforms (e.g., Splunk, Datadog, Microsoft Sentinel).

    1. Exposure to AI governance frameworks, data privacy regulations, or enterprise

    compliance standards (e.g., NIST AI RMF, EU AI Act, ISO 42001, SOC 2).

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