Security Engineer

Veeam; San Jose (CA); On-site; USD 150,000 - 210,000; Full time

Benefits offered by this job

Paid parental leave

Unlimited PTO

Medical, dental, vision coverage

401(k) retirement plan with matching

Job summary

Veeam is seeking a Security Engineer III to own detection engineering and the cloud security surface across our multi‑cloud estate. You will design and build a security data lake ingest telemetry from Azure, AWS, SaaS, and endpoints, shape detections in code, and automate response and triage to reduce MTTD and MTTR.

You will harden cloud environments, implement Terraform controls, and drive remediation with partner teams.

Qualifications

• Scripting and automation ability in Python or a comparable language, enough to build and maintain tooling.
• Strong cloud security fundamentals: RBAC and least privilege, secret and key management, egress control, and public-exposure prevention.
• Production Terraform experience. You’ve written and maintained modules other teams consume, and you know why a security control belongs in code rather than in a runbook.
• Real operational depth in both Azure and AWS: identity models, logging and audit sources, network boundaries, and where each provider’s defaults leave you exposed.
• Demonstrated detection building. You’ve written detections against real telemetry, tuned them against real false positives, and can explain a specific rule you shipped and how you validated it.
• 5+ years in security engineering, cloud operations, or detection engineering, with recent hands‑on ownership of production cloud security work.
• Fluency in at least one query language for security data (KQL, SQL, or equivalent) and the judgment to know when a query problem is actually a data-model problem.
• A track record of shipping production code or infrastructure you can point to. This is a hands‑on building role, not an advisory one.
• Microsoft Sentinel at production scale: analytics rules, automation rules, ingestion cost management, and multi-workspace design.
• Wiz experience, including turning posture and attack-path findings into an owned remediation workflow.
• Incident response experience in a cloud environment, on‑call or as an investigator.
• Kubernetes and container security exposure (AKS, EKS) and runtime detection for containerized workloads.
• Security data lake or SIEM migration experience, including cost and retention tradeoffs.
• Familiarity with regulated‑industry audit expectations (SOC 2 Type 2, ISO 27001, FedRAMP, HITRUST) and what auditors want from logging and monitoring controls.
• Relevant certifications (Azure or AWS security specialty, GCIA, GCDA, or similar)

Responsibilities

• Own the detection engineering and cloud security surface end to end: pipelines, detections, and guardrails in Azure/AWS.
• Design and build the security data lake: telemetry from Azure, AWS, SaaS, endpoints; normalize, retain, and control cost.
• Write, tune, and version-control detections as code; manage full lifecycle from hypothesis to deployment and retirement.
• Build the response side with detections: automate triage, enrich, and reduce MTTD/MTTR.
• Harden Azure and AWS environments: RBAC, secret management, egress control, logging, and public exposure across tenants/accounts.
• Deliver cloud security controls as Terraform modules; ensure fixes land in code for all environments.
• Turn posture findings into a prioritized remediation queue and close gaps with partner teams.
• Run detection coverage assessments against threat frameworks and close gaps relevant to the platform.

Skills

Python scripting

Cloud security fundamentals

Terraform

Azure & AWS

Detection engineering

5+ years security experience

KQL/SQL

Hands-on coding/infrastructure

Microsoft Sentinel

Wiz

Incident response

Kubernetes security

Data lake / SIEM migration

Regulated audit familiarity

Security certifications

Education

Azure or AWS security specialty

GCIA

GCDA

Tools

Kubernetes (AKS, EKS)

Microsoft Sentinel

Wiz

Terraform

GitHub Actions

Azure DevOps

Job description

• We’re looking for a Security Engineer III to own how we detect and respond to threats across our cloud estate, and to build the security data lake that makes that possible
• Our cloud-native SaaS platform runs on Microsoft Azure and AWS, delivering high-trust, secure data protection services to customers across regulated industries
• This role sits in Platform Security and owns the detection engineering and cloud security surface end to end: the pipelines that get security telemetry into one queryable place, the detections that fire off it, and the guardrails in Azure and AWS that stop the finding from recurring
• You’ll partner closely with SRE, Product Engineering, and the rest of Security Engineering, and your work is based on shipped mechanisms rather than on advice given
• Design and build our security data lake: decide what telemetry we ingest from Azure, AWS, SaaS, and endpoint sources, how it’s normalized and retained, and what it costs, so that detection engineers and incident responders can answer questions in minutes instead of days
• Write, tune, and version-control detections as code. Own the full lifecycle: hypothesis, query, test, deploy through CI/CD, measure false-positive rate, and retire what stops earning its keep
• Build the response side with the detections. Automate triage and enrichment, wire runbooks into the tooling, and cut mean-time-to-detect and mean-time-to-respond on the alert classes that matter most
• Hands on hardening our Azure and AWS environments: identity and RBAC boundaries, network egress, key and secret handling, logging coverage, and public-exposure control across multiple tenants and accounts
• Deliver cloud security controls as Terraform. Anything you fix once should land in the modules and pipelines so it stays fixed, in every environment, without a human remembering
• Turn cloud security posture findings into a prioritized, owned, and closing queue. Partner with the teams that own the resources and make remediation the path of least resistance
• Run detection coverage assessments against a recognized threat framework, find the gaps that matter for our platform and threat model, and close them
• Set direction on detection and cloud security tooling: what to adopt, what to retire, and what we build ourselves
• Technologies You’ll Work With
• Microsoft Sentinel, Log Analytics, and KQL for detection authoring and hunting
• Azure security services: Defender for Cloud, Entra ID, Key Vault, Azure Policy, Azure Monitor, Event Hubs
• AWS security services: CloudTrail, GuardDuty, Security Hub, IAM, Config, CloudWatch
• Terraform for all cloud security and detection infrastructure, with GitHub Actions and Azure DevOps as the delivery path
• Wiz for cloud security posture, attack-path analysis, and vulnerability signal
• Security data lake and pipeline components: object storage (ADLS / S3), OCSF-style normalization, Azure Data Explorer or an equivalent query engine, and Azure Functions / Lambda for glue
• Python for detection tooling, enrichment, and automation, with comfort reading PowerShell and Bash
• Sigma and detection-as-code patterns, plus Git-based review for every rule change

Benefits

• Paid parental leave: 8 weeks for all parents, 16 weeks for birthing parents
• Unlimited paid time off, plus 3 global VeeaMe Days for self-care
• Medical, dental, and vision coverage from day one
• 401(k) retirement plan with matching contributions up to annual limits
• Fertility, adoption, and surrogacy support through Maven, plus paid volunteer time
• Mental health support, therapy sessions, and digital wellness tools via SupportLinc EAP
• Legal services, identity protection, and supplemental health insurance options
• AirVet: 24/7 virtual veterinary care at no cost
• Professional training and education, including courses and workshops, internal meetups, and unlimited access to our online learning platforms (LinkedIn Learning, Athena, O’Reilly) and mentoring through our MentorLab program
• Tax-advantaged spending accounts for healthcare, dependent care, and commuting

Requirements

• Scripting and automation ability in Python or a comparable language, enough to build and maintain tooling rather than only configure vendor products
• Strong cloud security fundamentals: RBAC and least privilege, secret and key management, egress control, and public-exposure prevention
• Production Terraform experience. You’ve written and maintained modules other teams consume, and you know why a security control belongs in code rather than in a runbook
• Real operational depth in both Azure and AWS: identity models, logging and audit sources, network boundaries, and where each provider’s defaults leave you exposed
• Demonstrated detection building. You’ve written detections against real telemetry, tuned them against real false positives, and can explain a specific rule you shipped and how you validated it
• 5+ years in security engineering, cloud operations, or detection engineering, with recent hands‑on ownership of production cloud security work
• Fluency in at least one query language for security data (KQL, SQL, or equivalent) and the judgment to know when a query problem is actually a data-model problem
• A track record of shipping production code or infrastructure you can point to. This is a hands‑on building role, not an advisory one
• Microsoft Sentinel at production scale: analytics rules, automation rules, ingestion cost management, and multi-workspace design
• Wiz experience, including turning posture and attack-path findings into an owned remediation workflow
• Incident response experience in a cloud environment, on‑call or as an investigator
• Kubernetes and container security exposure (AKS, EKS) and runtime detection for containerized workloads
• Security data lake or SIEM migration experience, including cost and retention tradeoffs
• Familiarity with regulated‑industry audit expectations (SOC 2 Type 2, ISO 27001, FedRAMP, HITRUST) and what auditors want from logging and monitoring controls
• Relevant certifications (Azure or AWS security specialty, GCIA, GCDA, or similar)