Senior AI Security Engineer

Responsibilities

• Implement end‑to‑end identity context propagation for agent runs (who/what/why), ensuring every tool call and downstream action is attributable via signed requests, scoped tokens, tamper‑evident audit logs, and correlation IDs across orchestration layers, APIs, and cloud services.
• Partner with Platform and Cloud Engineering teams to secure AI/ML systems end‑to‑end.
• Develop secure execution environments for open‑source software, third‑party tools, and AI agents by leveraging OS‑level, network, IAM, and containerized controls.
• Build monitoring, logging, and detection capabilities to identify malicious or unintended use of systems, including AI‑enabled applications and agentic workflows.
• Stay current on emerging AI features and integrations introduced in third‑party tools and platforms, and proactively assess and mitigate associated security risks.
• Assess and continuously improve security posture across applications, infrastructure, and SDLC processes, including CI/CD pipelines.
• Required Qualifications
• Extensive hands-on experience across security engineering, cloud security, application security, and network security
• Proven ability to secure AI/ML and LLM‑based platforms, including data‑intensive and production systems
• Strong understanding of AI‑specific threat models (e.g., prompt injection, model misuse, data leakage, insecure outputs)
• Deep technical foundation in cloud‑native security across AWS and/or Azure, including IAM, network segmentation, secure connectivity, and threat detection
• Ability to build security controls through code and automation, leveraging scripting, IaC, and CI/CD security practices
• Strong written and verbal communication skills, with the ability to clearly articulate security risks, tradeoffs, and recommendations to both technical and non‑technical stakeholders
• Proven ability to collaborate effectively across teams, influencing cloud, platform, and application engineers to embed security seamlessly into delivery workflows

Requirements

• Experience designing and implementing automated guardrails, monitoring, logging, and detection for AI‑enabled and data‑driven applications
• Lead identification, assessment, and mitigation of AI‑specific risks, including prompt injection, data leakage, model abuse, insecure output handling, model evasion, and poisoning attacks.
• The base salary range for this position is $200,000 - $325,000 per year.
• Arrowstreet Capital operates a robust talent acquisition program, and we also seek to compensate and reward our employees competitively within our industry and in line with our merit-based culture. Our approach to total compensation includes base salaries and annual discretionary bonuses, a

Benefits

Additional Information

Job Description We are seeking a Senior Security Engineer with experience in cloud and AI security to help design, build, and scale security controls that protect our firm's systems, applications, cloud environments, and data-while enabling developer velocity or end‑user productivity. This role is responsible for strengthening the firm's security posture through automation, secure platform design, and proactive risk mitigation. A significant focus will be on securing AI/ML platforms and AI‑enabled applications across their full lifecycle, from development through deployment and runtime operations.

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