AI Senior Security Engineer

Overview

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At-a-Glance:Are you ready to build your career by joining a commercial data and analytics company. If so, our client is hiring an AI Senior Security Engineer.

Position Type
:
Contract

Hybrid

• Minimum + years of experience in software engineering or security engineering, with a strong focus on Python development and secure service design. Proven expertise in Google Cloud Platform (IAM, GKE/Cloud Run, Cloud Build, Artifact Registry, Secret Manager, VPC SC, SCC) and Dev Ops practices (IaC, CI/CD, policy as code). Practical understanding of AI threat models and mitigations, including prompt injection, content moderation, output redaction, secrets hygiene, and endpoint hardening.

• Familiarity with enterprise collaboration controls (Purview, Copilot DLP, Restricted Access sites) and validation methodologies. Experience integrating evaluation/red team harnesses into CI/CD pipelines, including gating based on evaluation regressions. Awareness of regulatory implications (EU AI Act, GDPR) for telemetry, logging, and DPIAs. Knowledge of SDLC-aligned security tooling (SAST, DAST, SCA) and dependency governance.

• Secure AI Access Layers:
  Develop Python-based middle-tier services for internal and service-to-service AI interactions, including request/response inspection, output redaction, rate limiting, and audit logging. Integrate with sensitivity labels, DLP, and identity controls.
• Agent Safety Engineering:
  Build reusable modules for agent orchestration frameworks, including tool use allow lists, sandboxing, constrained retrieval, and memory hygiene.
• Evaluation Pipelines:
  Implement CI/CD-integrated evaluation harnesses for red team prompts, jailbreak detection, toxicity/PII checks, hallucination scoring, and grounding validation. Gate releases based on evaluation thresholds and capture artifacts for Rs evidence.
• GCP Security Controls:
  Engineer robust security configurations for AI workloads using VPC SC, Private Service Connect, Workload Identity Federation, CMEK, Secret Manager, Cloud Build, Artifact Registry, and SCC alerting.
• Data Pipeline Hardening:
  Collaborate with data engineering teams to secure model input pipelines against poisoning and tampering, ensuring provenance, RBAC/ABAC enforcement, and DLP integration.
• Automation & Policy as Code:
  Automate enforcement of least privilege, environment isolation, egress controls, and artifact signing. Integrate with existing SAST/DAST/SCA and threat modeling workflows.
• Copilot Security Enablement:
  Configure and validate Purview sensitivity labels, Copilot DLP, Restricted Access sites, and Conditional Access policies for AI applications.
• Security Use Case Generation:
  Leverage LLMs to ingest architecture diagrams, data flow specifications, and service metadata to generate AI-assisted security use cases.
• SOC Agent Engineering:
  Build autonomous and assisted SOC agents to ingest and enrich alerts from Defender XDR, Sentinel, and approved third-party sources.

If you think you d be a good match, submit your resume and reach out to Prakash at () - to learn more.

LI-VK

Austin, TX

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3 weeks ago

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