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Principal Security Operation Analyst

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Hybrid

Principal Security Operation Analyst

Syneos Health

Principal Security Operation Analyst

Skills

Google Cloud PlatformPythonCybersecurityMachine LearningAIAWSGDPRComplianceAzure

1 month ago

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Important information


Contract type:

Permanent

Location:

Pune, Maharashtra, India

Work mode:

Hybrid

Published on:

16 September 2026

What they need


  • Lead implementation and operationalization of enterprise AI security tools and controls across Microsoft Copilot, Azure OpenAI, Foundry, Gemini Enterprise, Claude, AWS Bedrock, and other sanctioned AI platforms.
  • Design, deploy, and maintain AI security guardrails including prompt injection protection, jailbreak detection, content filtering, sensitive-data protection, and runtime safety controls.
  • Develop and maintain standardized AI security baselines, system prompts, security patterns, and reusable guardrail configurations for enterprise use cases.
  • Operationalize AI security technologies including Microsoft Defender for Cloud AI Services, Model Armor, Zscaler AI Guard, CASB controls, API gateway protections, and AI telemetry integrations.
  • Build and mature AI threat detection and response capabilities by integrating AI security telemetry into Sentinel and Cyber Threat Defense workflows.
  • Develop AI-specific security monitoring use cases, detection logic, alerting strategies, investigation runbooks, and containment procedures.
  • Establish and execute a repeatable AI red teaming program focused on prompt injection, jailbreak attacks, sensitive data leakage, unsafe outputs, agent misuse, model abuse, and guardrail bypass testing.
  • Design red team methodologies, testing frameworks, playbooks, rules of engagement, and evidence collection procedures for AI systems and agents.
  • Execute adversarial testing against AI models, agents, copilots, retrieval-augmented generation (RAG) solutions, and AI-enabled applications prior to production deployment.
  • Assess AI platforms and applications against OWASP LLM Top 10, CSA AI Controls, NIST AI RMF, and internal security standards.
  • Analyze AI-related findings, identify root causes, prioritize risk, and provide actionable remediation guidance to engineering and product teams.
  • Partner with AI developers and architects to implement secure-by-design AI patterns including pre-processing and post-processing controls, safety checkpoints, MCP governance, and tool-access restrictions.
  • Conduct security architecture reviews of AI solutions, agents, AI-assisted workflows, and external AI integrations.
  • Support enterprise AI governance initiatives including AI inventory, AI asset discovery, AI risk assessment, and non-human identity governance initiatives.
  • Develop metrics, dashboards, and executive reporting that demonstrate AI security posture, AI risk reduction, guardrail effectiveness, and red team outcomes.
  • Coordinate with Cyber Threat Defense, Security Operations, Cloud Operations, Enterprise Architecture, AI Governance, and application teams to operationalize AI security controls and response processes.
  • Evaluate emerging AI security technologies, AI gateways, AI firewalls, AI posture management solutions, and AI security tooling to support the evolving AI security roadmap.
  • Create and maintain SOPs, runbooks, and process documentation.
  • Ensure consistency across teams and shifts in how security tasks are performed.
  • Partner with SOC analysts, cyber threat intelligence & incident response, vulnerability managers, network engineers and others to understand pain points and requirements.
  • Work within Tech Solutions, DevOps, and compliance teams to align security processes with broader organizational goals.
  • Mentor and coach team members on best practices and process adherence.
  • Lead initiatives for process maturity (e.g., adopting industry standard frameworks, improving alert triage).
  • Stay current with industry best practices and emerging technologies.
  • Ensure processes meet regulatory and policy requirements.
  • Support internal and external audits by providing process evidence and documentation.

Qualification Requirements

  • 8+ years in cybersecurity, security engineering, cloud security, application security, or security operations.
  • 3+ years designing or securing AI/ML, Generative AI, LLM, agent-based, or cloud-native applications.
  • Experience with Microsoft Security, Azure AI/Foundry, Defender for Cloud, Sentinel, Zscaler, CASB, GCP, AWS, and modern security monitoring platforms.
  • Deep understanding of prompt injection, jailbreak attacks, LLM security risks, agentic AI security, RAG security, data leakage controls, and AI adversarial testing.
  • Strong written and verbal communication skills with the ability to operate at both technical and executive levels.
  • Self-directed and able to manage individual projects or work as part of a larger team.
  • Highly technical, detail-oriented, and organized individual with advanced skills in incident response and threat hunting.

Preferred:

Proficiency in a wide range of security tools such as vulnerability scanning, endpoint protection/EDR, SIEM, SOAR, IPS/IDS, WAF, SASE, perimeter firewall, reverse proxy, defense in depth practices, malware analysis tools, etc.

Programming experience in bash, python, or PowerShell.

Prior experience in the healthcare or pharmaceutical industry.

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