3 months ago
Remote, India +12 moreSenior
Responsibilities
- Build, deploy, and operate the AI runtime control plane and inline enforcement pipeline across Azure AI Foundry, AWS Bedrock, GCP Vertex, Copilot Studio, Databricks, and self-hosted environments.
- Harden AI gateway resilience through buffering, overload management, enforcement timeouts, rate limiting, and prompt-truncation controls.
- Integrate AI asset intelligence, model-security and supply-chain telemetry, red-team signals, SIEM correlation, SOC workflows, decision logs, and policy events.
- Author and tune runtime policies for prompt injection, jailbreaks, PII detection and redaction, data masking, intent filtering, tool-call validation, MCP access control, and agent permission boundaries.
- Translate adversarial-testing findings into policy updates, detection content, guardrail tuning, and validated remediation.
- Lead L3 investigations into AI attacks, perform decision-replay forensics and root-cause analysis, automate containment, and mentor L2 analysts.
- Evaluate AI security vendors and run proofs of concept for runtime defense, AIDR, AI-SPM, AI red-teaming, and model-security platforms.
- Engineer and operate security controls across Azure, AWS, GCP, AKS, and EKS, including posture management, detection tuning, remediation, identity, entitlements, and workload risks.
- Implement secure multi-cloud and zero-trust agent access patterns using least-privilege identities, conditional access, and OAuth scopes.
- Embed security into DevSecOps through Terraform scanning, container and Kubernetes security, secrets management, CI/CD hardening, and pre-deployment AI security testing.
- Support cloud workload vulnerability management across virtual machines, containers, registries, and serverless environments.
- Serve as an escalation point for investigations spanning cloud, identity, endpoint, and AI telemetry.
Requirements
- Significant hands-on engineering responsibility in cloud security across Azure, AWS, and GCP.
- Demonstrable experience securing or operating AI, ML, or LLM-based systems, or strongly evidenced ability to rapidly acquire AI-security expertise.
- Proven experience deploying, integrating, and tuning security platforms in complex enterprise environments and serving as an L3 or senior escalation point.
- Experience with enterprise security platform integration, API and connector engineering, log ingestion and normalization, SIEM/SOAR integration, and multi-vendor inline architectures.
- Strong knowledge of LLM and agentic-AI threat models, OWASP LLM Top 10 2025, OWASP Agentic Top 10, MITRE ATLAS, prompt-injection and jailbreak defense, RAG security, AI guardrails, gateways, MCP security, AI-SPM, AIDR, and AI red-teaming.
- Multi-cloud security engineering experience covering CSPM, CWPP, CNAPP, cloud identity and entitlements, Kubernetes and container security, hub-and-spoke architecture, segmentation, and baseline protection.
- Proficiency in KQL, PowerShell, and Python for automation, detection engineering, and tooling.
- Experience with DevSecOps, Terraform security, and CI/CD pipeline integration.
- Experience operating security tooling in Kubernetes-based environments such as AKS and EKS is advantageous.
- Experience integrating open-source components into enterprise stacks is advantageous.
- Vendor proof-of-concept experience is a plus.
- Relevant certifications such as CISSP, CCSP, SC-100, AZ-500, AWS Certified Security – Specialty, Google Professional Cloud Security Engineer, or AI security credentials strengthen an application.
- Bachelor’s degree in Computer Science, Cybersecurity, Information Systems, or equivalent practical experience.
- Excellent English communication skills, including runbooks, integration documentation, and communicating trade-offs to technical and leadership stakeholders.
- Ability to work effectively in a fast-paced, dynamic, globally distributed environment.
Benefits
- Flexible remote work is available.
- Elective benefits are tailored to the employee’s country.
- Formal leadership and professional development programs and on-demand courses are available.
- Financial, physical, and mental well-being support is provided through seminars, events, and the global Life Empowerment Assistance Program.
- Employees can participate in inclusive communities, business resource groups, volunteering, and environmental and social initiatives.
- The role includes onboarding and networking with new coworkers within the first 30 days.
- Some travel is required, and nonstandard business hours may be needed for projects, business-impact issues, and incident response.
Tech Stack
Categories
About TD SYNNEX
TD SYNNEX distributes IT hardware, software, and cloud services and aggregates solutions for technology vendors and resellers, including VARs and system integrators. It provides logistics, financing, cloud marketplaces, and professional services that help partners procure, bundle, and deploy technology for end customers. The public company (NYSE: SNX), headquartered in Fremont, California, was formed in 2021 through the merger of Synnex and Tech Data and operates globally.