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Salary: USD 141,000 - 177,000 / annual
Sysdig is seeking an AI Platform Engineer to build and operate the infrastructure that powers the company's AI-driven cloud security platform. You will own multiple critical systems: the MCP (Model Context Protocol) fleet for self-hosted and managed servers; the agent platform that enables other teams to ship AI agents independently; the Bedrock runtime and gateway with model access, cost attribution, and content filtering; and the observability pipeline connecting Bedrock usage to Snowflake for tracking and alerting.
Your responsibilities span platform architecture, security, and operational excellence. You'll make AI spend and usage visible through identity-matched tracking and threshold alerting. You'll own the secure deployment path for non-technical employees, including MDM configuration, desktop client setup, credentials, and auth flows. You'll build governance into the platform by routing workflows based on data sensitivity, enforcing least privilege, maintaining auditability, and keeping unproven models sandboxed from production data through configuration rather than code rewrites.
This is a full-stack platform role requiring hands-on ownership of production systems that other teams depend on. You'll work across backend services, APIs, CI/CD pipelines, and containerized deployments. You should be comfortable building from scratch—writing MCP servers or API integrations rather than just wiring managed connectors. You'll balance shipping velocity with operational rigor, automating manual processes and taking ownership of the unglamorous work: upgrades, credentials, quotas, and on-call responsibilities.
Sysdig is a cloud security company that created Falco, the open standard for cloud threat detection, and is trusted by over 60% of the Fortune 500. The company has been recognized as a Best Place to Work and one of Deloitte's fastest-growing companies for five consecutive years.
Requirements:
- 6+ years in software engineering, platform engineering, or DevOps, with demonstrated ownership of production systems others depended on
- Hands-on AWS expertise required: IAM, ECS or Lambda, CloudWatch, and working VPC knowledge
- Full-stack capability: backend services, APIs, CI/CD, containerized deployments
- Ability to build from scratch, not just integrate managed connectors
- Hands-on experience with LLMs: LLM APIs, prompt engineering, agent development; must have shipped something with them
- Self-direction and ability to take underspecified tasks and figure out missing details
- Bias toward shipping and automating repetitive work
- Ownership mentality for operational concerns (upgrades, credentials, quotas, on-call)
- Strong judgment on build vs. buy decisions
- Willingness to raise problems and disagreements early
