A productized security review and controls package for companies adopting AI coding agents and developer-environment automation.
Added Jun 28, 2026
Companies are giving AI developer tools access to source code, credentials, CI systems, cloud accounts, and local development environments before security practices are mature. Security teams need to decide which risks matter, which alerts are noise, and what controls are required without slowing engineering teams down. Existing tools produce findings, but the harder job is turning fragmented signals into practical, developer-friendly security decisions.
Offer a fixed-scope security assessment and implementation package for AI-native developer tooling. The service maps where AI agents touch code, secrets, infrastructure, sandboxes, and third-party integrations, then delivers a prioritized control plan, tuned detection rules, integration checks, and developer-facing remediation guidance. Over time, the repeatable pieces can become templates, integration playbooks, managed monitoring, and lightweight software for evidence collection and finding triage.
AI coding agents and developer copilots are rapidly moving from experiments into production engineering workflows. The security surface is new enough that many teams are hiring for judgment and systems design rather than buying a mature off-the-shelf category.
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Build and maintain security tools, automation, prototypes, and reusable engineering patterns that teams adopt in real workflows. Partner directly with product and research teams to design, debug, implement, and validate security improvements, staying engaged through root-cause resolution rather than stopping at recommendations.
Partner with engineers to implement scalable controls across cloud infrastructure, applications, and AI systems. Run risk assessments and drive remediation across systems, vendors, and processes.
Design, build, and maintain DevSecOps tooling in Kubernetes and Google Cloud Platform (GCP), including support for AI/ML workloads Lead the integration of security into CI/CD pipelines — code scanning, secret detection, software composition analysis, and infrastructure policy enforcement — partnering with engineering teams to adopt them without friction
Build solutions that enhance the firm’s security posture across LLM applications, AI agents, developer workflows, and enterprise AI infrastructure. Collaborate with security, infrastructure, platform engineering, cloud, and application development teams to deliver secure and production-ready AI capabilities.
Deliver high-quality systems and tools that improve developer productivity, strengthen reliability, and support adoption of AI-assisted engineering workflows across Microsoft Security.
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