# MTS, Security

**Company:** [Fireworks AI](https://hotfix.jobs/companies/fireworks-ai)
**Location:** San Mateo, CA
**Role:** Security Engineering
**Salary:** $180k – $220k/yr
**Experience:** 3+ years
**Skills:** Python, Go, GCP, Kubernetes, Docker, Terraform, Linux, IAM, DevSecOps, CI/CD, Zero Trust, AWS, Azure, llm security
**Posted:** 2026-01-20

> Security Engineer designing and building security controls, tooling, and automation for AI infrastructure, multi-cloud platforms, Kubernetes, and LLM serving at Fireworks AI. Requires 3-7 years experience in security or infrastructure engineering, proficiency in Python/Go, and deep cloud-native and Kubernetes knowledge.

## Job Description

## Key Responsibilities
- Design and build security-focused software and platform capabilities to protect customer data, models, and services across our multi-cloud infrastructure, including encryption, identity and access management, secure API gateways, secure model execution, and sandboxing strategies.
- Perform security reviews of cloud-native architectures—including Kubernetes clusters, multi-cloud workloads, and distributed data stores—and build integrated systems for continuous security monitoring, anomaly detection, and automated response.
- Embed security into CI/CD pipelines using a DevSecOps approach, implementing automated scanning, policy enforcement, and secure-by-default build and deployment workflows.
- Apply a build-over-buy philosophy by designing and developing in-house security tooling and automation where it provides better control, scalability, and integration than off-the-shelf solutions.
- Build and operate a comprehensive vulnerability management program, partnering with various teams to remediate risks across applications, containers, cloud infrastructure, and dependencies.
- Operate and continuously improve security operations, including detection engineering, alert triage, incident response, and continuous improvement through post-incident reviews.
- Participate in red/blue team exercises, tabletop simulations, and post-incident root cause analysis to strengthen security resilience.
- Embed compliance and regulatory controls into infrastructure and product layers (e.g., SOC 2, ISO 27001, ISO42001, HIPAA, PCI-DSS, GDPR).

## Minimum Qualifications
- 3 to 7 years of experience in software engineering or security engineering with a strong focus on security, infrastructure, or cloud-native systems.
- Proficient in Python and/or Go with experience in designing production-grade systems.
- Strong understanding of cloud-native architectures using GCP, particularly in the area of network segregation, authentication, authorization, encryption, data protection, intrusion detection, and cloud-specific security benchmarks.
- Hands-on experience with Kubernetes, Docker, and containerized production environments; deep knowledge of Kubernetes internals and native security controls is a strong plus.
- Familiarity with security tooling in managed CI/CD environments (e.g., GitHub Actions, Harness, CircleCI).
- Solid experience working in Linux environments, including system administration, debugging, and automation via command-line tooling.
- Familiarity with modern identity and access controls (SAML, OAuth, OIDC, SSO, RBAC/ABAC).

## Preferred Qualifications
- Experience designing secure multi-cloud deployments and zero-trust architectures.
- Experience designing, operating, and securing large-scale Kubernetes platforms, including control plane security, node hardening, and multi-tenant isolation.
- Experience designing, operating, and securing large-scale multi-cloud platforms across AWS, GCP, Azure, Oracle Cloud, and GPU as service cloud providers.
- Proficiency with infrastructure-as-code using Terraform and Python, including experience building modular policy-as-code frameworks.
- Strong understanding of data protection techniques, including encryption at rest/in transit, tokenization, key management, and confidential computing.
- Experience integrating security into microservice architectures, service meshes, and distributed systems.
- Hands-on experience securing LLM/ML platforms, model inference infrastructure, GPU clusters, or data labeling pipelines.
- Experience designing detection engineering pipelines across cloud audit logs, network telemetry, and application signals.
- Experience building large-scale IAM and PAM platforms using least-privilege, workload identity, and just-in-time access.
- Familiarity with container image vulnerability remediation, security, SBOM generation, and software supply chain security.
- Experience building, implementing and operating security automation platforms for incident response and security operations.
- Familiarity with compliance tooling and frameworks (e.g., Vanta, SOC 2, ISO 27001, ISO 42001, PCI-DSS).

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