Apply

Ready to go for it?

AI Apply speeds things up—apply directly if you prefer.

FREE ACCESS
5,000–10,000 jobs/day
Scoutfield Logo

See all jobs on Scoutfield

Search thousands of fresh jobs every day.

Discover
  • Fresh listings
  • Fast filters
  • No subscription required
Create a free account and start exploring right away.
EY

AI Engineer – Manager, Consulting

EY

. 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 StatesMid-LevelSenior💰 $144,900 - $265,800 per yearWebsite

Core Competencies

Role fit
Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in deploying AI/ML solutions within cybersecurity, with a strong focus on technical delivery, client engagement, and mentoring. Proficient in Python, APIs, and cloud engineering, while ensuring quality and security in AI operations.

Highest-signal resume keywords
AI/ML Solution DeploymentPython ProficiencyCloud Engineering on AWS, Azure, or GCPCybersecurity ExpertiseTechnical Delivery Leadership

ATS Keywords

Tailor your resume
Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills
Software EngineeringAI/ML SolutionsAutomated TestingProduction DeliveryVulnerability AnalysisSecure Code ReviewDevSecOpsCI/CDAPI IntegrationData Protection
Soft Skills
Strong Writing SkillsPresentation SkillsTechnical Documentation Skills
Tools & Technologies
GitSIEMSOAREDRVulnerability ManagementCode Security PlatformsRetrieval PipelinesEvaluation HarnessesModel Tool IntegrationsFrontier AI Models
Certifications & Qualifications
Cybersecurity CertificationsCloud CertificationsAI/ML Certifications
Industry Keywords
CybersecurityThreat InvestigationDetection EngineeringIncident Response AutomationSecurity ArchitectureIdentity and Access ManagementOWASP Top 10MITRE ATLASAdversarial TestingForward-Deployed Engineering

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
  • Work 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 technical delivery, workstreams, timelines, and budgets
  • Mentor Senior Consultants and Consultants
  • Lead architecture, pair programming, code reviews, and integration troubleshooting
  • Partner with frontier model providers and researchers to evaluate cyber capabilities and translate deployment findings into engineering requirements
  • Support proposals, demonstrations, thought leadership, and account growth
  • Develop reusable components, evaluation suites, and delivery playbooks
  • Develop engineering teams while remaining hands-on and accountable for quality

Requirements

What you’ll need
  • Bachelor's degree in Cybersecurity, Computer Science, Information Systems, Engineering, or a related field and 5+ years of relevant experience; or a graduate degree and 4+ years
  • Hands-on software engineering experience
  • At least 1–2 years building or deploying AI/ML solutions
  • Proficiency in Python, APIs, Git, automated testing, and production delivery
  • Experience in one or more of: frontier AI models or LLM applications for cybersecurity; 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; 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 leading 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, cyber-focused model selection, adaptation, and evaluation, agent orchestration, model serving, LLM observability, CI/CD evaluation gates, adversarial testing, AI red teaming, sandboxing, regulated or restricted environments, engineering workshops, live prototyping, architecture reviews, executive demos, cyber evaluation datasets, fine-tuning, open-source AI or security projects, forward-deployed engineering, or consulting experience is advantageous

Benefits

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