
1001 - 5000 employees
Founded 2010
💼 Consulting
📦 Logistics
🏭 Manufacturing
Consulting • Logistics • Manufacturing
Vantage Data Centers is a company specializing in the design, development, and operation of highly flexible and scalable data centers. These data centers cater to hyperscalers, cloud providers, and large enterprises, offering state-of-the-art facilities across 5 continents and 21 markets. Vantage focuses on providing large-scale campuses that enable customers to grow steadily, with over 23 million square feet dedicated to data center space and 2. 6GW+ of power capacity. Committed to sustainability and efficiency, Vantage ensures 100% uptime with standardized designs offering predictability and performance. The company is backed by prominent investors such as DigitalBridge Group and Silver Lake, maintaining a strong financial standing and excellent customer satisfaction rates.
🕒 June 30
🐊 Florida – Remote
💵 $115k - $120k / year
⏰ Full Time
🟡 Mid-level
🟠 Senior
🤖 AI Engineer
🦅 H1B Visa Sponsor
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1001 - 5000 employees
Founded 2010
💼 Consulting
📦 Logistics
🏭 Manufacturing
Consulting • Logistics • Manufacturing
Vantage Data Centers is a company specializing in the design, development, and operation of highly flexible and scalable data centers. These data centers cater to hyperscalers, cloud providers, and large enterprises, offering state-of-the-art facilities across 5 continents and 21 markets. Vantage focuses on providing large-scale campuses that enable customers to grow steadily, with over 23 million square feet dedicated to data center space and 2. 6GW+ of power capacity. Committed to sustainability and efficiency, Vantage ensures 100% uptime with standardized designs offering predictability and performance. The company is backed by prominent investors such as DigitalBridge Group and Silver Lake, maintaining a strong financial standing and excellent customer satisfaction rates.
• Perform technical security testing and reviews of AI‑enabled applications, agents, and workflows • Implement approved security architecture patterns for AI, ML, and LLM systems across cloud, hybrid, on‑prem, and OT‑adjacent environments • Engineer secure inference paths, APIs, service identities, authentication flows, and segmentation boundaries aligned with least privilege and zero trust principles • Implement technical safeguards to mitigate prompt injection, unauthorized context expansion, data leakage, hallucination risk, and unsafe output handling • Configure and maintain controls for limiting, monitoring, logging, and managing AI usage across platforms, models, and agents • Implement and validate technical controls supporting model explainability, traceability, and output validation where AI impacts operational, workforce, safety, or compliance decisions • Review and validate LLM usage patterns, including prompt design, retrieval‑augmented generation (RAG), context window constraints, and output handling mechanisms • Implement controls preventing unauthorized external model training, reuse, or retention of enterprise data by third‑party AI platforms • Validate encryption, access logging, retention, and deletion controls for data ingested, processed, or generated by AI systems • Execute AI‑specific threat modeling activities and contribute findings to enterprise and OT cybersecurity risk assessments • Ensure AI systems produce security telemetry, logs, and audit trails sufficient to detect misuse, drift, policy violations, or anomalous behavior • Integrate AI security signals into SOC, SIEM, and incident response tooling and workflows • Support investigation and response to AI‑related incidents, including data exposure, model failure, unsafe outputs, or control breakdowns • Conduct technical security reviews of vendor‑provided and embedded AI capabilities, assessing model behavior, data handling, and control alignment • Enforce approved security requirements for AI vendors and prevent activation of AI features without required security validation and governance approval • Drive alignment with ISO 42001 and related AI governance standards across applicable teams
• Bachelor’s degree in Cybersecurity, Computer Science, Data Science, Engineering, or related field, or equivalent experience • Minimum 5+ years of experience in cybersecurity, security architecture, or risk engineering roles • Hands‑on experience securing data pipelines, APIs, cloud platforms, and analytics or ML‑enabled systems • Strong understanding of identity, access management, encryption, logging, and secure system design • Direct experience securing AI/ML platforms, LLMs, or analytics pipelines (preferred) • Experience with cloud security (Azure, AWS, GCP) and SaaS‑based AI platforms (preferred) • Familiarity with OT, critical infrastructure, or safety‑critical environments (preferred) • Security certifications such as Security+, SecurityAU+, CISM, or cloud security certifications (preferred)
• medical, dental, and vision coverage • life and AD&D insurance • short and long-term disability coverage • paid time off • employee assistance program • participation in a 401k program that includes company match • additional voluntary benefits
Apply Now🕒 June 30
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