Principal Technical Consultant – Forward Deployed Engineer, AI Security

This is a fully remote position, open to applicants in United States.

📋 Description

• Act as the principal technical leader for the implementation and operationalization of AI security solutions within customer or enterprise settings.

• Create technical proposals, statements of work, and solution architectures for AI security projects and business development initiatives.

• Convert business, operational, and AI security needs into deployable architectures and implementation strategies.

• Collaborate with stakeholders to ensure solutions align with AI governance, compliance standards, and long-term platform objectives.

• Serve as a trusted advisor and an executive-level point of contact throughout the onboarding, implementation, rollout, and optimization phases.

• Design and execute integrations across AI platforms, model registries, LLM gateways, vector databases, and AI-enhanced security tools.

• Construct and configure cloud-native data ingestion, normalization, and enrichment pipelines for AI telemetry, model activity logs, and prompt/response data.

• Integrate APIs, webhooks, message queues, and automation workflows across AI operations, identity management, cloud services, and application ecosystems.

• Develop reusable deployment patterns, templates, and technical resources.

• Operationalize AI security controls and guardrails, including defenses against prompt injection, model access controls, data leakage prevention, and agentic workflow monitoring.

• Secure non-human identities, such as service accounts, API keys, tokens, and credentials for autonomous agents.

• Implement red teaming, adversarial testing, model risk assessment, and anomaly detection for AI systems.

• Define data requirements, feedback mechanisms, and operational guardrails for production-level AI systems.

• Establish governed automation for AI security monitoring, investigation, and response activities.

• Support requirements for resiliency, observability, performance, and scalability.

• Diagnose integration issues, deployment obstacles, and production challenges.

• Enhance reliability and maintainability through thorough documentation, testing, monitoring, and standardized engineering practices.

• Lead cooperative efforts among AI Engineering, Security Engineering, Data Science, Infrastructure, Sales, product, and customer teams.

• Convey technical concepts to both technical and non-technical audiences, including executive stakeholders.

• Mentor engineers and consultants, contributing to best practices in AI security implementation and solution design.

• Provide field insights to shape platform roadmap, product direction, and architectural standards.

• Represent the practice in pre-sales activities, proposal development, and client presentations.

⛳️ Requirements

• Over 10 years of experience in security engineering, AI engineering, platform engineering, forward-deployed engineering, solutions consulting, or similar technical roles, with a proven track record of progression to a principal or senior consulting level.

• Practical experience in securing AI systems, LLM applications, or AI production pipelines.

• Experience in deploying cloud-native architectures on at least one major cloud platform, such as AWS, Azure, or GCP.

• Strong expertise in data integration, telemetry pipelines, normalization, and security analytics workflows applied to AI systems.

• Experience collaborating directly with customers, executive stakeholders, or cross-functional delivery teams in implementation-focused settings.

• Demonstrated ability in developing technical proposals, statements of work, and scoping documents for client engagements.

• Capability to lead technical projects, drive execution, and influence outcomes without direct authority.

• Proven ability to facilitate cross-team collaboration among 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.

• Preferred: Experience deploying solutions in regulated or compliance-sensitive environments.

• Preferred: Knowledge of infrastructure as code, CI/CD workflows, and AI production delivery practices.

• Preferred: Experience in developing reusable implementation frameworks or field engineering playbooks.

• Relevant cloud, security, or AI-specific certifications are advantageous.

🏝️ Benefits

• Medical, Dental, and Vision Insurance.

• 401(k).

• Paid company holidays.

• Paid time off.

• Paid parental and caregiver leave.

• Sponsorship for certifications and credentials to encourage ongoing learning.

• Cross-department training and development opportunities.

• Access to a multi-million-dollar technology lab.

• Options to opt-out of AI application and resume review without penalty.

• Options to opt-out of interview recording and transcription without penalty.