Senior Forward Deployed Engineer, AI Security
New
A
AHEADAI security
United StatesFull-TimeSenior
Salary170,000 - 200,000 USD per year
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Job Details
- Experience
- 7+ years of experience in security engineering, AI engineering, platform engineering, forward deployed engineering, solutions consulting, or related technical roles
- Required Skills
- PythonBashRESTful APIs
Requirements
- Have 7+ years of experience in security engineering, AI engineering, platform engineering, forward deployed engineering, solutions consulting, or a related technical role.
- Have hands-on experience securing AI systems, LLM applications, or AI production pipelines.
- Have experience deploying cloud-native architectures on at least one major cloud provider, such as AWS, Azure, or GCP.
- Have a strong background in data integration, telemetry pipelines, normalization, and security analytics workflows applied to AI systems.
- Have experience working directly with customers, executive stakeholders, or cross-functional delivery teams.
- Have experience developing technical proposals, statements of work, and customer-engagement scoping documents.
- Understand AI security risks, including prompt injection, model theft, data poisoning, adversarial attacks, and agentic AI risks.
- Have scripting and automation experience using Python, PowerShell, or Bash.
- Be familiar with APIs, REST, webhooks, and event-driven workflows.
- Have working knowledge of LLMs, vector search, retrieval-augmented generation, model evaluation, and AI assistants or agents.
- Have a bachelor’s degree in Computer Science, Information Security, Engineering, or equivalent practical experience.
Responsibilities
- Deploy and operationalize AI security solutions in customer and enterprise environments.
- Develop technical proposals, statements of work, solution architectures, and implementation plans.
- Design and implement integrations across AI platforms, model registries, LLM gateways, vector databases, and security tooling.
- Build cloud-native pipelines for AI telemetry, model activity logs, and prompt and response data.
- Implement security controls and guardrails for AI systems, including prompt injection defense, model access controls, and data leakage prevention.
- Secure non-human identities, including service accounts, API keys, tokens, and autonomous agent credentials.
- Implement automation for AI security monitoring, investigation, and response.
- Troubleshoot deployment and integration issues with AI, platform, cloud, and security teams.
- Lead cross-team collaboration, mentor engineers and consultants, and provide field feedback on platform and architectural direction.
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