AI Defense Engineer
Job Type: Direct Hire
Location: Boston/Washington DC
Work Authorization: Must be eligible to work in the US; no sponsorship provided.
Job Description
About the Role
The Senior AI Defense Engineer is a technical leader responsible for securing AI in a global law firm environment. The role sets technical direction, drives delivery, and mentors colleagues to raise awareness and capabilities. It translates emerging AI threats into practical defenses, guardrails, policy enforcement layers, monitoring and detections, adversarial test automation, and hardened environments to withstand real attacker pressure.
The role supports a smart‑integration, buy‑before‑build security strategy, evaluating, selecting, and operationalizing commercial AI security solutions that meet stringent legal‑sector expectations—including matter confidentiality, ethical walls, client audit requirements, data residency constraints, and contractual IT service obligations.
Success looks like: enhancing and performing commercial AI tool evaluations and approvals, assessing internally developed AI solutions, and responding to audit demands with credible evidence of AI cybersecurity protections. It also includes secure‑by‑default adoption by engineering teams, adversarial assessments that reliably find issues before production, telemetry and detections that catch abuse early, and an AI security roadmap that stays current with fast‑moving technology shifts.
What You Will Be Doing
- Threat Modeling & Risk Assessment – Guide and conduct technical threat modeling for AI/ML systems, identify AI‑specific threats, and provide prioritized mitigation guidance via vendor configuration standards, reference patterns, and exception processes.
- AI Defense Engineering – Evaluate and operationalize security controls, guardrails, and enforcement mechanisms for AI services, enable detections and monitoring for AI‑specific attack patterns, and secure integration and operational use of enterprise AI services.
- Adversarial Testing & Red Teaming – Identify and utilize adversarial test suites for AI applications, simulate realistic attacker behavior, capture and track issues as actionable vulnerabilities, and partner with product teams to validate fixes.
- Tooling & Automation – Incorporate AI capabilities into existing and future security stacks (SIEM, SOAR, EDR, WAF, API gateways, identity platforms).
- Incident Response & Forensics for AI Systems – Lead technical response for AI‑related incidents, analyze logs and model behavior, reconstruct attack paths, and improve playbooks and post‑incident reviews.
- Collaboration – Serve as the AI security technical lead with engineering, product, infrastructure, and security leadership; communicate tradeoffs, align stakeholders, and unblock delivery.
- Roadmap Leadership – Own the technical strategy and roadmap for AI security engineering; translate threat intelligence and risk assessments into prioritized engineering work, milestones, and measurable outcomes.
- Contribute to the Firm’s Service Matters initiative by consistently improving the firm’s image internally and externally with professionalism and a can‑do attitude.
Required Skills
- Practical understanding of ML/AI pipelines: data collection, feature engineering, training, evaluation, deployment, monitoring.
- Strong understanding of how enterprise AI services (SaaS/PaaS) are deployed and governed, including data handling, routing, and isolation controls.
- Experience with at least one major cloud platform (AWS, Azure, or GCP) and modern infrastructure (containers, Kubernetes, secrets management, CI/CD).
- Experience integrating Microsoft AI security and governance capabilities, including Azure OpenAI / Model Catalog, Azure API Management, Microsoft Entra ID, and related Azure‑native AI security controls and gateways.
- Familiarity with AI attack patterns and defenses such as prompt injection, jailbreaks, data/model poisoning, model inversion, membership inference, automation bias, and unsafe autonomy in agents.
- Solid security fundamentals: authentication/authorization, network security, data protection, logging/telemetry, secure software engineering practices, vulnerability management.
- Strong understanding of neural network frameworks (e.g., LangChain, Semantic Kernel, LlamaIndex) or agentic/orchestration platforms.
- Experience conducting application security reviews or threat modeling for APIs, microservices, or data platforms.
- Familiarity with NIST AI RMF, ISO 42001, ISO 27001, and key privacy/security regulations and third‑party assurance artifacts (SOC 2, ISO certifications, pen test summaries) to support buy decisions.
- Ability to translate complex risks into concrete technical changes (config updates, new controls, guardrails, playbooks) and operational playbooks.
- Demonstrated team leadership or supervisory role is a plus.
- Strong written and verbal communication skills; able to collaborate with data scientists, software engineers, and security teams.
Required Experience
- Typically 5–10+ years in security engineering, application security, red teaming, threat research, or ML/ML Ops engineering.
Education
- Bachelor’s degree in computer science, information security, or related field; or equitable work experience.
- Certification: ISC2 Building AI Strategy preferred.
Equal Employment Opportunity Statement
Gravity IT Resources is an Equal Opportunity Employer. We are committed to creating an inclusive environment for all employees and applicants. We do not discriminate on the basis of race, color, religion, sex (including pregnancy, sexual orientation, or gender identity), national origin, age, disability, genetic information, veteran status, or any other legally protected characteristic. All employment decisions are based on qualifications, merit, and business needs.