Note: The job is a remote job and is open to candidates in USA. AHEAD builds platforms for digital business by combining cloud infrastructure, automation, analytics, and software delivery. The Principal Technical Consultant – Forward Deployed Engineer, AI Security role leads the deployment and operationalization of AI security solutions, including securing AI systems, LLM applications, and agentic workflows. The role also develops architectures and integrations, advises customers, leads cross-functional delivery, and mentors technical teams.
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 that scope AI security engagements and support business development efforts
- Translate business, operational, and AI security requirements into deployable architectures and implementation plans
- Partner with internal and external stakeholders to ensure solutions are aligned to AI governance, compliance requirements, and long-term platform strategy
- Act as a trusted advisor and executive-level point of contact during onboarding, implementation, rollout, and optimization phases
- 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
- Integrate APIs, webhooks, message queues, and automation workflows across AI operations, identity, cloud, and application ecosystems supporting AI systems
- Develop reusable deployment patterns, templates, and technical assets to accelerate future AI security implementations
- Operationalize security controls and guardrails for AI systems, including prompt injection defense, model access controls, data leakage prevention, and agentic workflow monitoring
- Secure non-human identities (NHI), including service accounts, API keys, tokens, and autonomous agent credentials, across AI and agentic workflows
- Work with AI, detection engineering, and data teams to implement red teaming, adversarial testing, model risk scoring, and anomaly detection for AI systems
- Help define data requirements, feedback loops, and operational guardrails needed to secure AI systems in production environments
- Ensure deployed solutions are practical, measurable, and aligned to AI governance and risk objectives
- Implement secure and governed automation for AI security monitoring, investigation, and response use cases across heterogeneous environments
- Support resiliency, observability, performance, and scale requirements for deployed AI security solutions
- Troubleshoot integration issues, deployment blockers, and production challenges in partnership with AI, platform, cloud, and security teams
- Improve reliability and maintainability through documentation, testing, monitoring, and standardized engineering practices
- Lead cross-team collaboration across AI Engineering, Security Engineering, Data Science, Infrastructure, Sales, and product or customer teams
- Communicate technical concepts clearly to both technical and non-technical stakeholders, including executive audiences
- Mentor and develop engineers and consultants, contributing to best practices for AI security implementation, delivery, and technical solution design
- Provide field feedback to influence platform roadmap, product direction, and architectural standards
- Represent the practice in pre-sales activities, proposal development, and client presentations
Skills
- 10+ years of experience in security engineering, AI engineering, platform engineering, forward deployed engineering, solutions consulting, or related technical roles, with demonstrated 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 cross-team collaboration across engineering, security, data science, and business stakeholders
- Bachelor's degree in Computer Science, Information Security, Engineering, or equivalent practical experience
- Experience with AI red teaming, adversarial AI testing, or AI governance frameworks such as the NIST AI RMF, ISO/IEC 42001, or the OWASP Top 10 for LLM Applications
- Familiarity with the MITRE ATLAS (Adversarial Threat Landscape for Artificial-Intelligence Systems) knowledge base for AI-specific attack techniques and mitigations
- Experience deploying solutions in regulated or compliance-sensitive environments
- Familiarity with infrastructure as code, CI/CD workflows, and AI production delivery practices
- Experience building reusable implementation frameworks or field engineering playbooks
- Relevant certifications are a plus, including cloud, security, or AI-specific certifications
Benefits
- Remote work
- Medical, Dental, and Vision Insurance
- 401(k)
- Paid company holidays
- Paid time off
- Paid parental and caregiver leave
- Access to a multi-million-dollar technology lab
- Cross-department training and development
- Sponsored certifications and credentials for continued learning
- Internal groups like Moving Women AHEAD and RISE AHEAD
Company Overview
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