Job description

AHEAD builds platforms for digital business. By weaving together advances in cloud infrastructure, automation and analytics, and software delivery, we help enterprises deliver on the promise of digital transformation. At AHEAD, we prioritize creating a culture of belonging, where all perspectives and voices are represented, valued, respected, and heard. We create spaces to empower everyone to speak up, make change, and drive the culture at AHEAD. We are an equal opportunity employer, and do not discriminate based on an individual's race, national origin, color, gender, gender identity, gender expression, sexual orientation, religion, age, disability, marital status, or any other protected characteristic under applicable law, whether actual or perceived. We embrace all candidates that will contribute to the diversification and enrichment of ideas and perspectives at AHEAD. The Principal Technical Consultant (Forward Deployed Engineer) for AI Security is a senior, customer-facing technical leader responsible for deploying, integrating, and operationalizing AI security capabilities in real-world customer and enterprise environments, with a focus on securing AI systems, LLM applications, and agentic workflows. This role works at the intersection of engineering, AI, security, data, and customer success to translate complex requirements into scalable, production-ready solutions. This individual partners closely with security leaders, AI engineers, data scientists, platform teams, and infrastructure stakeholders to implement AI security controls, secure AI development pipelines, integrate security tooling for AI systems, and accelerate time to value. The ideal candidate brings 10+ years of security experience and combines deep technical expertise in AI systems, model and data security, and cloud platforms with proven experience developing technical proposals and statements of work, leading cross-team collaboration, and driving customer-facing delivery at a principal level. Responsibilities Customer and Stakeholder Delivery 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 Solution Implementation and Integration 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 AI Security Operations 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 Automation and Reliability 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 Cross-Functional Leadership 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 Required Qualifications 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 Preferred Qualifications 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 Education Bachelor’s degree in Computer Science, Information Security, Engineering, or equivalent practical experience The compensation range indicated in this posting reflects the On-Target Earnings (“OTE”) for this role, which includes a base salary and any applicable target bonus amount. This OTE range may vary based on the candidate’s relevant experience, qualifications, and geographic location. Why AHEAD: Through our daily work and internal groups like Moving Women AHEAD and RISE AHEAD, we value and benefit from diversity of people, ideas, experience, and everything in between. We fuel growth by stacking our office with top-notch technologies in a multi-million-dollar lab, by encouraging cross department training and development, sponsoring certifications and credentials for continued learning. USA Employment Benefits include: - Medical, Dental, and Vision Insurance - 401(k) - Paid company holidays - Paid time off - Paid parental and caregiver leave - Plus more! See benefits aheadbenefits.com for additional details. Use of AI: We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, assessing responses, or to capture recordings and create transcriptions or summaries during interviews. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please refer to the Candidate Privacy Notice or contact us at privacy@ahead.com . You may opt-out of the review or analysis of your application and resume by AI tools by using the General Application . Please include the role you wish to apply for in the Additional Information field. You may also choose to opt-out of recording and transcription at any time, including after joining an interview. Candidates will not be penalized for choosing to opt-out.

Requirements

Must-haves

AHEAD builds platforms for digital business. By weaving together advances in cloud infrastructure, automation and analytics, and software delivery, we help enterprises deliver on the promise of digital transformation.
We embrace all candidates that will contribute to the diversification and enrichment of ideas and perspectives at AHEAD.
Customer and Stakeholder Delivery
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
Solution Implementation and Integration
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
AI Security Operations
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

Nice-to-haves

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
Bachelor’s degree in Computer Science, Information Security, Engineering, or equivalent practical experience

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aillmapiawsazuregcpci/cd

Platform: lever
Effort: quick

Benefits

Benefits detected in the listing.

Dental

Vision

401(K)

Paid Time Off