Senior Cyber AI Engineer – Consulting

. Work as a forward-deployed engineer helping clients apply frontier AI cyber models to real security challenges .

Posted 9/15/2026full-timeNew York City • California • United StatesSenior💰 $104,800 - $192,200 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in deploying AI solutions for cybersecurity, including proficiency in Python, API integration, and cloud engineering. Capable of collaborating with cross-functional teams to deliver technical solutions while ensuring security and compliance.

Highest-signal resume keywords

Python ProficiencyAI/ML Solution DeploymentCloud Engineering on AWS, Azure, or GCPSecurity Operations and Threat InvestigationTechnical Documentation and Presentation Skills

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

AI Model DeploymentSoftware EngineeringAutomated TestingProduction DeliveryVulnerability AnalysisIncident Response AutomationDevSecOpsCI/CDAPI IntegrationData Protection

Soft Skills

Strong Writing SkillsPresentation SkillsCommunication Skills

Tools & Technologies

GitSIEMSOAREDRVulnerability ManagementCode Security Platforms

Certifications & Qualifications

Cybersecurity CertificationCloud CertificationAI/ML Certification

Industry Keywords

CybersecurityAI Red TeamingAdversarial TestingData ResidencyPrivacy Regulations

Tech Stack

Tools & technologies

AWSAzureCloudCyber SecurityGoogle Cloud PlatformPython

About the role

Key responsibilities & impact

Work as a forward-deployed engineer helping clients apply frontier AI cyber models to real security challenges
Build, evaluate, and deploy AI solutions from prototype to production
Collaborate with client security and engineering teams to deploy AI workflows for threat investigation, detection engineering, vulnerability analysis, and remediation support
Use retrieval, tool calling, and structured outputs
Build evaluation datasets and test harnesses measuring accuracy, false positives, task completion, latency, and cost
Own assigned technical deliverables, estimate tasks, and communicate progress and risks to engagement leaders
Contribute to architecture, pair programming, code reviews, and integration troubleshooting
Support Consultants
Work with model providers and researchers to test cyber capabilities and document deployment findings
Contribute to technical demonstrations, proposals, reusable components, evaluation suites, and delivery playbooks

Requirements

What you’ll need

Bachelor's degree in Cybersecurity, Computer Science, Information Systems, Engineering, or a related field
3–5 years of relevant experience, including hands-on software engineering and experience building or deploying AI/ML solutions
Proficiency in Python, APIs, Git, automated testing, and production delivery
Experience in one or more of: deploying frontier AI models or LLM applications for cybersecurity; building agents, model tool integrations, retrieval pipelines, and evaluation harnesses; security operations, threat investigation, detection engineering, or incident response automation; DevSecOps, CI/CD, containers, and infrastructure-as-code for AI services; cloud engineering and secure AI deployment on AWS, Azure, or GCP; API integration with SIEM, SOAR, EDR, vulnerability management, or code security platforms; application security, vulnerability analysis, secure code review, or automated remediation
Understanding of prompt injection, data leakage, unsafe tool use, and safeguards informed by OWASP Top 10 for LLMs and MITRE ATLAS
Working knowledge of security architecture, identity and access management, data protection, and secure AI operations
Experience contributing to client-facing delivery or cross-functional engineering from requirements through deployment and handover
Strong writing, presentation, and technical documentation skills
Willingness to travel based on client and business needs, estimated at 25–50%
Cybersecurity, cloud, engineering, or AI/ML certifications are advantageous
Experience with frontier model providers or cyber-focused model selection, adaptation, and evaluation is advantageous
Experience with agent orchestration, model serving, LLM observability, and CI/CD evaluation gates is advantageous
Knowledge of adversarial testing, AI red teaming, sandboxing, and safeguards for authorized dual-use cyber work is advantageous
Experience with data residency, privacy, model access, and deployment in regulated or restricted environments is advantageous
Experience contributing to engineering workshops, live prototyping, architecture reviews, and client demos is advantageous
Experience building cyber evaluation datasets, fine-tuning models, or contributing to open-source AI or security projects is advantageous
Forward-deployed engineering or consulting experience supporting production deployments and client teams is advantageous

Benefits

Comp & perks

Medical and dental coverage
Pension plan
401(k) plan
Wide range of paid time off options
Professional growth
Inclusive culture
Reasonable accommodation for qualified individuals with disabilities, including veterans with disabilities