Principal Technical Consultant – Forward Deployed Engineer, AI Security
New
A
AHEADAI security
United StatesFull-TimePrincipal
Salary200,000 - 230,000 USD per year
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Job Details
- Experience
- 10+ years of experience in security engineering, AI engineering, platform engineering, forward deployed engineering, solutions consulting, or related technical roles
- Required Skills
- AWSGCPAzure
Requirements
- 10+ years of experience in security engineering, AI engineering, platform engineering, forward deployed engineering, solutions consulting, or related technical roles, with progression to a principal or senior consulting level.
- Hands-on experience securing AI systems, LLM applications, or AI production pipelines.
- Experience deploying cloud-native architectures on at least one major cloud provider, such as AWS, Azure, or GCP.
- Strong background in data integration, telemetry pipelines, normalization, and security analytics workflows applied to AI systems.
- Experience working directly with customers, executive stakeholders, or cross-functional delivery teams in implementation-focused environments.
- Proven experience developing technical proposals, statements of work, and scoping documents for customer engagements.
- Ability to lead technical engagements, drive execution, and influence outcomes without direct authority.
- Demonstrated ability to lead collaboration across engineering, security, data science, and business stakeholders.
- Bachelor’s degree in Computer Science, Information Security, Engineering, or equivalent practical experience.
- Preferred: experience with AI red teaming, adversarial AI testing, or AI 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, infrastructure as code, CI/CD workflows, or AI production delivery practices.
Responsibilities
- Serve as the senior technical lead for deploying and operationalizing AI security solutions in customer or enterprise environments.
- Develop technical proposals, statements of work, and solution architectures for AI security engagements.
- Translate business, operational, and AI security requirements into deployable architectures and implementation plans.
- Design and implement integrations across AI platforms, model registries, LLM gateways, vector databases, and AI-enabled security tooling.
- Build and configure cloud-native data ingestion, normalization, and enrichment pipelines for AI telemetry, model activity logs, and prompt/response data.
- Implement AI security controls and guardrails, including prompt injection defense, model access controls, data leakage prevention, and agentic workflow monitoring.
- Secure non-human identities, including service accounts, API keys, tokens, and autonomous agent credentials.
- Implement governed automation for AI security monitoring, investigation, and response, and support solution resiliency, observability, performance, and scale.
- Lead collaboration across AI Engineering, Security Engineering, Data Science, Infrastructure, Sales, and product or customer teams.
- Mentor engineers and consultants, represent the practice in pre-sales activities, and provide field feedback to influence platform roadmaps and architectural standards.
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