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AI Security Engineer
AI Security EngineerAkaasa Technologies • United States
AI Security Engineer

AI Security Engineer

Akaasa Technologies • United States
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POSITION

AI Security Engineer

REQUIRED SKILLS

Role overview

You will build and integrate the security guardrails that make AI usable at scale : policy as code, proxy layers for model access, prompt / content filtering, evaluation harnesses, secrets & key management, telemetry, and automation in CI / CD. You'll prototype quickly (PoCs), harden what works, and partner with platform, data, and product teams to get controls into production on Google Cloud with modern DevOps practices.

What you'll do

  • Build secure AI access layers (Python) for internal use and service to service scenarios : request / response inspectors, output redaction, rate limiting, and audit logging. Integrate with sensitivity labels / DLP and identity controls where applicable.
  • Develop agent safety patterns (for orchestration frameworks) including tool use allow lists, function sandboxing, constrained retrieval, and memory hygiene; create reusable modules for product teams.
  • Implement and operate evaluation pipelines (red team prompts, jailbreak detection, toxicity / PII checks, hallucination / grounding scores) as part of CI / CD-gating releases on eval thresholds; capture artifacts for 5Rs evidence.
  • Engineer GCP security controls for AI workloads : VPC SC, private service connect, service account hygiene, Workload Identity Federation, CMEK, Secret Manager, Cloud Build / Artifact Registry policies, Cloud Logging / Monitoring / SCC alerting.
  • Harden data pipelines feeding models (poisoning / tamper detection, provenance / lineage, RBAC / ABAC, DLP), working with data engineering teams.
  • Automate controls (policy as code) to enforce least privilege, environment isolation, egress controls, and artifact signing; integrate with existing SAST / DAST / SCA and threat modeling workflows.
  • Contribute to Copilot security enablement : configure Purview sensitivity, Copilot DLP, Restricted Access sites, and Conditional Access for AI apps; validate via test plans.
  • Ingest architecture diagrams, data flow specs and service metadata to produce LLM assisted Security use-cases (leveraging AI for security).
  • Engineer autonomous / assisted SOC agents to ingest alerts from Defender XDR / Sentinel and approved third party sources, perform enrichment

What you'll bring

  • Strong software engineering in Python (frameworks, testing, packaging) with experience building secure services / middle tiers and AI agent integrations.
  • Hands on Google Cloud expertise (IAM, GKE / Cloud Run, Cloud Build, Artifact Registry, Secret Manager, VPC SC, SCC) and DevOps (IaC, CI / CD, policy as code).
  • Practical knowledge of AI threats & mitigations (prompt injection filters, content moderation, output redaction, token level guardrails, secrets hygiene, model endpoint hardening).
  • Familiarity with enterprise collaboration controls (Purview labels, DLP for Copilot, restricted access sites) and how to test their efficacy.

    • Nice to have

  • Experience wiring evaluations / red team harnesses into CI (e.g., blocking merges on eval regressions); exposure to EU AI Act / GDPR implications for logging / telemetry and DPIAs.
  • Knowledge of SAST / DAST / SCA and dependency governance aligned to our SDLC standards.
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    Ai Security Engineer • United States