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Senior AI Infrastructure Security Engineer

DTEL Engineering & Consultants IncDunkirk, NY🇺🇸United StatesPosted 4 Aug 2026

Quick Overview

Work Type
Hybrid
Level
Mid Senior

Job Description

  • Serve as Subject Matter Expert for the design, maintenance, and implementation of security architectures for AI infrastructure, including model hosting environments, model registries, feature stores, vector databases, and agent orchestration platforms
  • Lead risk assessments and threat modeling for AI platforms and integrations, including supply chain risks around models, datasets, and third-party AI services
  • Engineer robust Identity and Access Management (IAM) for AI systems, including RBAC/ABAC policies for models, agents, tools, and data stores, along with comprehensive secrets and key lifecycle management
  • Partner with DevOps and Platform Engineering teams to embed AI security controls into CI/CD pipelines and infrastructure-as-code, including secure deployment patterns and policy-as-code for AI resources
  • Build and integrate logging and observability pipelines for AI systems covering prompts, tool calls, model outputs, agent actions, and data access paths into existing detection and incident response infrastructure
  • Define and implement guardrails and isolation strategies for agentic workflows, including sandboxing, least privilege tool access, network segmentation, and blast radius reduction
  • Lead and participate in AI-related incident response and forensics, including investigations into model misuse, compromised agents, or suspicious data flows
  • Ensure compliance with relevant security and AI governance frameworks including NIST CSF, NIST RMF, NIST AI RMF, ISO 27001, and SOC 2 Type 2 by delivering technical controls and audit-ready evidence
  • Create and maintain comprehensive security documentation including architecture decision records, threat models, runbooks, and SOPs in a compliant and audit-ready state
  • Provide technical mentoring and oversight to less experienced engineers responding to AI platform security issues
  • What You'll Need to Have
  • 7+ years of experience in information security, computer science, or engineering, with 5+ years specifically in security engineering, cloud security, or platform security
  • 3+ years of hands-on experience with container orchestration and modern infrastructure stacks (Kubernetes-based platforms, microservices, or serverless) and their security hardening
  • Strong proficiency in Identity and Access Management (IAM), secrets management, and securing service-to-service communication in distributed systems
  • Deep knowledge of data protection practices relevant to AI workloads, including DLP, encryption, masking, and access pattern monitoring
  • Proven ability to build security tooling and automation, and to work in close partnership with infrastructure and SRE teams
  • Expert-level understanding of NIST CSF, NIST RMF, NIST AI RMF, ISO 27001, and SOC 2 Type 2 controls and their application to technical security programs
  • Experience securing AI/ML or LLM-based systems from an infrastructure or security perspective (model endpoints, registries, or AI gateways)

Skills

Microservices
Encryption
SOC 2
Kubernetes
LESS
LLM

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