AI and Cloud Security Engineer

Overview

TD SYNNEX (NYSE: SNX) is the worlds largest IT distributor and we are accelerating AI adoption across Azure AI Foundry AWS Bedrock Copilot Studio Databricks and self-hosted agent environments. Our security philosophy is distinctive: rather than slowing innovation with pre-approval gatekeeping we operate a runtime-first default-allow security posture every AI interaction is intercepted analyzed and enforced at the moment of our architecture the traditional network perimeter no longer defines the defensive boundary: the AI agent is the perimeter.

The AI & Cloud Security team is chartered to make that vision operational. We are seeking senior technical owner of the AI security runtime control plane and detection fabric. You will build and integrate the inline enforcement pipeline (AI gateway runtime data protection intent-based enforcement) tune the policies that keep it fast and low-friction and serve as the final escalation point for the most complex AI and cloud security incidents. You will also help implement and participate in operation of a closed-loop defensive system in which continuous red-team findings automatically improve runtime policies detection logic and SOC threat models. You join a team of two AI & Cloud Security Architects and will be the engineering force that turns strategy into operating controls across a multi-cloud estate (Azure AWS GCP).

This role involves collaborating with cross-functional teams to ensure the security of AI and cloud environments AI applications and infrastructure addressing potential threats and maintaining compliance with regulatory standards. The ideal candidate will have a strong background in AI technologies and their implementation as well as cloud security security principles and cybersecurity best practices. The ability to develop automation in both AI and cloud environments with infrastructure as code (IaC) or policy as code principles is required. The engineer will report to AI & Cloud Security leadership and have strong working relationships with IT and application development leadership.

Responsibilities

• Integration build and own the AI runtime control plane. Engineer deploy and operate the inline enforcement pipeline for AI traffic: an AI gateway chained with runtime data-protection and intent-based enforcement platforms fronting LLMs tools and MCP servers across Azure AI Foundry AWS Bedrock GCP Vertex Copilot Studio Databricks and self-hosted environments.
• Harden the gateway layer for resilience: configure buffering and overload management enforcement timeouts on external-processing filters layered global/local rate limiting and prompt-truncation filters to defend against token-exhaustion and reasoning overload denial-of-service attacks.
• Integrate the wider AI security ecosystem into one coherent system: onboard AI asset-intelligence context (agent inventory ownership blast radius) into enforcement decisions; connect model-security and supply-chain telemetry and continuous red-team signals into SIEM correlation and SOC workflows; stream unified AI detections decision logs and policy events for forensics and audit.
• Policy tuning enforce without friction. Author and calibrate runtime policies: prompt-injection and jailbreak prevention PII detection/redaction and data masking intent-based filtering tool-call validation MCP access control and agent permission boundaries (including lethal trifecta prevention for low-code agents). Balance detection versus hard-block modes to minimize false positives and tune per AI archetype embedded SaaS copilots democratized low-code agents homegrown agentic pipelines device-based coding agents and homegrown models.
• Operate the closed loop: translate continuous adversarial-testing findings into runtime policy updates new detection content and guardrail tuning then validate remediation through re-testing so defenses evolve with attackers rather than remaining static.
• L3 coverage final escalation for the AI Security toolset. Lead deep investigations of AI-specific attacks (direct/indirect prompt injection RAG poisoning memory poisoning agent hijacking MCP/tool abuse model manipulation AI-driven data exfiltration) perform decision-replay forensics and root-cause analysis drive automated containment (agent quarantine permission revocation kill switch) toward our sub-15-minute containment objectives and mentor L2 analysts. Troubleshoot any incidents related to policies.
• Evaluate and pilot AI security vendors: run structured proofs-of-concept for runtime defense AIDR AI-SPM AI red-teaming and model-security platforms and provide technical recommendations as the stack matures.
• Engineer and operate cloud security controls across Azure AWS and GCP posture policies detection tuning and remediation of misconfigurations excessive entitlements and workload risks including the Kubernetes estates (AKS/EKS) hosting the AI gateway layer.
• Design and maintain secure multi-cloud patterns consistent with company approved architectural blueprint as well as zero-trust agent access: least-privilege identity for humans service principals and agents (Entra ID AWS IAM GCP IAM PAM) conditional access for AI platforms and least-privilege OAuth scopes for agent integrations.
• Embed security into DevSecOps: Infrastructure-as-Code (Terraform) scanning container/Kubernetes security secrets management CI/CD hardening and pre-deployment AI security testing gates in Azure DevOps/GitHub Actions.
• Support cloud workload vulnerability management (VMs containers registries serverless) with risk-based prioritization and act as escalation point for investigations spanning cloud identity endpoint and AI telemetry.

Critical Skills

• Proven ability to integrate enterprise security platforms into one system: API/connector engineering log ingestion and normalization SIEM/SOAR integration and multi-vendor inline architectures.
• Strong AI/GenAI security depth: LLM and agentic-AI threat models (OWASP LLM Top 10 2025 OWASP Agentic Top 10 MITRE ATLAS) prompt-injection/jailbreak defense RAG security AI guardrails and gateways MCP security and the AI-SPM/AIDR/AI-red-teaming tooling categories. Hands-on experience with AI security technologies is highly valued; so is experience with open-source AI security tooling.
• Multi-cloud security engineering across Azure AWS and GCP: CSPM/CWPP/CNAPP operations cloud identity and entitlements Kubernetes and container security and secure architecture (hub-and-spoke segmentation baseline protection).
• Proficiency in KQL PowerShell and Python for automation detection engineering and tooling; DevSecOps and IaC security (Terraform); CI/CD pipeline integration.
• A pragmatic enablement-first security mindset: comfortable with a default-allow culture where controls must be fast precise and low-friction rather than restrictive.
• Excellent English communication clear runbooks integration documentation and the ability to explain trade-offs to architects engineers and leadership across a globally distributed team and multiple time zones.
• Excellent communication and collaboration skills
• Ability to work effectively in a fast-paced dynamic environment.

Experience

• Significant hands-on engineering responsibility including in cloud security (Azure/AWS/GCP) and demonstrable experience securing or operating AI/ML or LLM-based systems (or strongly evidenced rapidly acquired hands-on AI-security capability).
• Proven track record deploying integrating and tuning security platforms in complex enterprise environments and serving as an L3 / senior escalation point; experience running vendor proofs-of-concept is a plus.
• Experience operating security tooling in Kubernetes-based environments (AKS/EKS) and integrating open-source components into enterprise stacks is an advantage.
• Relevant certifications strengthen an application (none individually required): CISSP CCSP SC-100 AZ-500 AWS Certified Security Specialty Google Professional Cloud Security Engineer; AI red-team or AI-security credentials are a plus.
• Bachelors degree in Computer Science Cybersecurity Information Systems or equivalent practical experience.

Working conditions

• Willing to work nonstandard business hours for projects business impact issues and incident response.
• Some travel required.
• Flexible remote work.

At Tech Data a TD SYNNEX Company our values guide everything we do: Together We Own It We Dare to Go We Grow and Win and above all We Do the Right Thing. These principles shape how we work with each other our partners and our communities as we drive innovation and create lasting impact.

Whats In It For You

• Elective Benefits: Our programs are tailored to your country to best accommodate your lifestyle.
• Grow Your Career: Accelerate your path to success (and keep up with the future) with formal programs on leadership and professional development and many more on-demand courses.
• Elevate Your Personal Well-Being: Boost your financial physical and mental well-being through seminars events and our global Life Empowerment Assistance Program.
• Diversity Equity & Inclusion: Its not just a phrase to us; valuing every voice is how we succeed. Join us in celebrating our global diversity through inclusive education meaningful peer-to-peer conversations and equitable growth and development opportunities.
• Make the Most of our Global Organization: Network with other new co-workers within your first 30 days through our onboarding program.
• Connect with Your Community: Participate in internal peer-led inclusive communities and activities including business resource groups local volunteering events and more environmental and social initiatives.

Dont meet every single requirement Apply anyway.

At Tech Data a TD SYNNEX Company were proud to be recognized as a great place to work and a leader in the promotion and practice of diversity equity and inclusion. If youre excited about working for our company and believe youre a good fit for this role we encourage you to apply. You may be exactly the person were looking for!

We are an equal opportunity employer and committed to building a diverse team that represents and empowers a variety of backgrounds perspectives and skills. All qualified applicants will receive consideration for employment based on merit without regard to race colour religion national origin gender gender identity or expression sexual orientation protected veteran status disability genetics age or any other characteristic protected by law. To support our diversity and inclusion efforts we may ask for voluntary gender disclosure information. This data will be used solely to improve our hiring practices and ensure fair treatment for all candidates.