AHEAD
AHEAD
AHEAD is a technology consulting and systems-integration company helping enterprises modernize how they build, secure, and operate digital environments. Its work spans artificial intelligence, infrastructure, applications, data platforms, cloud, cybersecurity, and platform modernization, with services ranging from strategy and financial consulting through implementation, operations, and managed services. AHEAD also supports IT procurement and lifecycle management through AHEAD Hatch and hardware integration through AHEAD Foundry. The company works with major technology providers including AWS, Google Cloud, Microsoft, Cisco, Dell, VMware, NVIDIA, ServiceNow, Palo Alto Networks, and Rubrik, serving organizations in healthcare, financial services, manufacturing, retail, and the public sector. Its hiring context is oriented toward technology consulting, enterprise engineering, systems integration, and related delivery and operations roles.

Principal AI Security Consultant / Forward-Deployed Engineer

Lead enterprise AI security deployments for AHEAD customers across cloud, automation, analytics, and software delivery environments. Own customer-facing architecture, integrations, governance, and production security operations.

Description

  • Lead the deployment and operationalization of AI security solutions in customer and enterprise environments
  • Prepare technical proposals, statements of work, and solution architectures for AI security engagements and business development
  • Convert business, operational, and AI security needs into deployable architectures and implementation plans
  • Coordinate with stakeholders to align solutions with AI governance, compliance obligations, and long-term platform strategy
  • Serve as a trusted advisor and executive point of contact through onboarding, implementation, rollout, and optimization
  • Design and deliver integrations spanning AI platforms, model registries, LLM gateways, vector databases, and AI security tools
  • Build cloud-native pipelines to ingest, normalize, and enrich AI telemetry, model activity logs, and prompt and response data
  • Connect APIs, webhooks, message queues, and automation workflows across AI operations, identity, cloud, and application environments
  • Create reusable deployment patterns, templates, and technical implementation assets
  • Put AI security controls and guardrails into operation, including prompt injection defenses, model access controls, data loss prevention, and agent workflow monitoring
  • Protect non-human identities such as service accounts, API keys, tokens, and autonomous agent credentials
  • Conduct red teaming, adversarial testing, model risk scoring, and anomaly detection for AI systems
  • Establish data requirements, feedback loops, and operating guardrails for production AI applications
  • Implement governed automation for AI security monitoring, investigation, and response
  • Address resiliency, observability, performance, and scalability needs
  • Resolve integration problems, deployment blockers, and production issues
  • Strengthen reliability and maintainability through documentation, testing, monitoring, and consistent engineering practices
  • Drive collaboration among AI Engineering, Security Engineering, Data Science, Infrastructure, Sales, product, and customer teams
  • Explain technical concepts clearly to technical, non-technical, and executive audiences
  • Mentor engineers and consultants while advancing AI security implementation and solution design practices
  • Share field insights to inform platform roadmaps, product direction, and architectural standards
  • Represent the practice in pre-sales activities, proposal development, and client presentations

Requirements

  • 10+ years in security engineering, AI engineering, platform engineering, forward-deployed engineering, solutions consulting, or a related technical field, with progression to principal or senior consulting responsibilities
  • Practical experience securing AI systems, LLM applications, or production AI pipelines
  • Experience deploying cloud-native architectures on at least one major provider, including AWS, Azure, or Google Cloud
  • Strong expertise in data integration, telemetry pipelines, normalization, and security analytics for AI systems
  • Experience working directly with customers, executives, or cross-functional delivery teams in implementation-focused settings
  • Demonstrated ability to create technical proposals, statements of work, and engagement-scoping documents
  • Ability to lead technical engagements, maintain delivery momentum, and influence decisions without direct authority
  • Track record of leading collaboration across engineering, security, data science, and business teams
  • Bachelor’s degree in Computer Science, Information Security, Engineering, or equivalent practical experience
  • Preferred experience with AI red teaming, adversarial testing, or governance frameworks such as NIST AI RMF, ISO/IEC 42001, or OWASP Top 10 for LLM Applications
  • Preferred familiarity with the MITRE ATLAS knowledge base
  • Preferred experience delivering solutions in regulated or compliance-sensitive environments
  • Preferred familiarity with infrastructure as code, CI/CD, and AI production delivery practices
  • Preferred experience creating reusable implementation frameworks or field engineering playbooks
  • Cloud, security, or AI certifications are advantageous

Benefits

  • Medical, dental, and vision insurance
  • 401(k) plan
  • Paid company holidays
  • Paid time off
  • Paid parental and caregiver leave
  • Company support for certifications and professional credentials
  • Cross-department training and development
  • Access to a multi-million-dollar technology lab
  • Option to decline AI application and resume review without penalty
  • Option to decline interview recording and transcription without penalty

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