AHEAD

Builds and manages enterprise technology

Senior Forward Deployed Engineer - AI Security

Implementation & Technical Account ManagementPosted on Nov 10

Full-timeRemote in USA$170k - $200k /yrRemote

About the Job

Requirements

At least 7 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, large language model applications, or AI production pipelines.
Experience deploying cloud-native architectures on at least one major cloud provider, such as AWS, Azure, or Google Cloud Platform.
A 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.
A strong understanding of AI security risks, including prompt injection, model theft, data poisoning, adversarial attacks, and agentic AI risks, as well as foundational cloud, identity, and endpoint security.
Experience with scripting and automation using tools such as Python, PowerShell, or Bash.
Familiarity with APIs and integration patterns, including REST, webhooks, and event-driven workflows.
Working knowledge of AI concepts, including large language models, vector search, retrieval-augmented generation, model evaluation, and AI assistants or agents.
A bachelor's degree in Computer Science, Information Security, Engineering, or equivalent practical experience.

Responsibilities

Serve as the technical engineer for deploying and operationalizing AI security solutions in customer or enterprise environments.
Support development of 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 align with AI governance, compliance requirements, and long-term platform strategy.
Support engagement leaders during onboarding, implementation, rollout, and optimization phases.
Design and implement integrations across AI platforms, model registries, large language model 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, 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 technical and non-technical stakeholders.
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.

Desired Qualifications

Experience with implementation and integration of OpenAI models, specifically Daybreak Blue and/or Red.
Experience with implementation and integration of Anthropic models.
Experience with AI red teaming, adversarial AI testing, or AI governance frameworks such as the NIST AI Risk Management Framework, ISO/IEC 42001, or the OWASP Top 10 for Large Language Model Applications.
Familiarity with the MITRE ATLAS knowledge base for AI-specific attack techniques and mitigations.
Experience deploying solutions in regulated or compliance-sensitive environments.
Familiarity with infrastructure as code, continuous integration/continuous delivery workflows, and AI production delivery practices.
Experience building reusable implementation frameworks or field engineering playbooks.
Relevant cloud, security, or AI-specific certifications.

Salary Range: 170000 to 200000 (Currency: USD) (Pay period: per-year-salary)

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 Senior Technical Consultant (Forward Deployed Engineer) for AI Security is a senior, customer-facing technical engineer 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 leads, 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 7+ 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 technical engineer for deploying and operationalizing AI security solutions in customer or enterprise environments

Support development 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

Support engagement leaders 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

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

Required Qualifications

7+ 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

Technical Skills

Strong understanding of AI security risks, including prompt injection, model theft, data poisoning, adversarial attacks, and agentic AI risks, alongside foundational cloud, identity, and endpoint security

Experience with scripting and automation using tools such as Python, PowerShell, or Bash

Familiarity with APIs and integration patterns including REST, webhooks, and event-driven workflows

Working knowledge of AI concepts including LLMs, vector search, retrieval-augmented generation, model evaluation, and AI assistants or agents

Strong problem-solving skills, execution mindset, and ability to operate effectively in ambiguous, fast-moving environments

Preferred Qualifications

Experience with implementation and integration of OpenAI models, specifically Daybreak Blue and/or Red

Experience with implementation and integration of Anthropic models

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 https://www.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 [email protected].

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.

About the Company

AHEAD

Builds and manages enterprise technology

AHEAD designs and runs technology systems for large enterprises, connecting infrastructure, applications, data and security under a single delivery team. Its roots in data centers shape its approach to modernizing complex environments that span private facilities and public clouds. Engineers assess a client's existing systems, plan upgrades and build the platforms, while managed services teams monitor operations, maintain software and respond to security incidents. The company earns money through consulting and implementation projects, technology sales and ongoing services that keep those environments running. AHEAD was founded in 2007 and is headquartered in Chicago, Illinois.

Company size: 1,001-5,000
Company stage: Seed
Total funding: $9M
Headquarters: Chicago, IL
Founded: 2007

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