Senior Security Engineer

Required Skills & Experience

• 7+ years of hands-on Security Engineering experience within SaaS, cloud, or cybersecurity environments.
• Strong cloud security experience securing modern cloud-native applications and infrastructure.
• Experience across AWS (required), with Azure and/or GCP exposure preferred.
• Deep understanding of Kubernetes, containers, infrastructure-as-code, Terraform, networking, IAM, and cloud architecture.
• Strong Python or similar programming experience with a proven track record building internal tools, automation, APIs, and security platforms.
• Experience building detections, security monitoring capabilities, incident response tooling, and security automation.
• Demonstrated builder mentality with a "build versus buy" approach to solving security challenges.
• Experience designing and developing detections-as-code, security workflows, custom integrations, and internal security services.
• Strong knowledge of SIEM, EDR, WAF, cloud security, SaaS security, identity security, and security operations technologies.
• Experience performing threat modeling, architecture reviews, and implementing secure-by-design principles.
• Strong understanding of AI security concepts, secure AI adoption, and leveraging AI to improve security operations.
• Excellent communication skills and ability to explain technical architecture, tradeoffs, security risks, and engineering decisions.

Nice to Have Skills & Experience

• Experience building internal security products, developer-focused security tooling, or security platforms.
• Hands-on experience securing AI applications, LLMs, AI agents, or enterprise AI implementations.
• Strong understanding of AI security risks such as prompt injection, data leakage, model misuse, and excessive permissions.
• Experience with Zero Trust architecture and modern identity security frameworks.
• GIAC certifications (GCIH, GCFA), CISSP, CCSP, or similar certifications.
• Strong GitHub portfolio, personal security projects, home labs, open-source contributions, or technical security content.
• Experience coming from highly technical consulting environments or high-growth SaaS companies.

Job Description

Insight Global is seeking a Senior Security Engineer for Sigma Computing, a rapidly growing cloud-native SaaS company focused on next-generation analytics and AI applications. This is the client's highest-priority security hire and an opportunity to join a highly technical Security Engineering team responsible for building and scaling security capabilities across the organization. The ideal candidate is a true security builder who enjoys writing code, developing platforms, creating automation, and solving complex security challenges through engineering rather than relying solely on commercial security tools. This role spans cloud security, detection engineering, IAM, incident response, SaaS security, and AI security, making it an excellent opportunity for engineers who enjoy working across multiple security domains. We're looking for someone who understands the underlying technology, can build scalable security solutions from the ground up, and is excited about leveraging AI to transform security operations. This position is based in San Francisco (preferred) or New York City and requires fully onsite.

Day to Day

• Design, build, deploy, and maintain scalable security platforms, automation frameworks, APIs, and internal tooling.
• Develop security solutions supporting cloud security, identity security, SaaS security, incident response, and security operations.
• Create detections-as-code, monitoring capabilities, alerting pipelines, and response automation.
• Build custom security workflows and integrations that improve operational efficiency and security coverage.
• Partner with engineering teams to implement secure-by-design architectures and security best practices.
• Perform threat modeling and security reviews for cloud infrastructure, applications, APIs, and AI-enabled systems.
• Design and implement controls for AI applications, LLM-powered services, agents, and enterprise AI workflows.
• Build guardrails and monitoring capabilities to identify prompt injection, model misuse, data leakage, and other AI-related risks.
• Leverage AI and automation to accelerate investigations, improve detection capabilities, and reduce operational overhead.
• Evaluate emerging security technologies and drive adoption of solutions that provide measurable business and security value.
• Collaborate across Security, Engineering, Infrastructure, and Product teams to improve security maturity across the organization.
• Help shape the future of the client's cloud security, detection engineering, and AI security strategy