Senior Backend Engineer, Cloud Infrastructure

North San Jose, CA · Full-time · 5 days in office

$225K–$250K base competitive equity $15K–$30K discretionary bonus

Visa support: case by case

This is an AI cybersecurity company building an agentic platform for enterprise security teams.

The product replaces fragmented, manual security workflows with systems that can continuously contextualize, assess, reason, and execute security work across modern enterprise environments.

The company was founded by the creators of Claroty and SecurityMatters, two category-defining cybersecurity companies, and is already trusted by Fortune 500 enterprises.

The team is early, technical, and well-capitalized: 55 people, founded in 2025, with $125M raised.

You will build the cloud backend and data systems behind an agentic AI platform used in high-stakes cybersecurity environments.

This is a senior engineering role for someone who can own systems from architecture through production: APIs, event pipelines, infrastructure, deployment, observability, reliability, and operational correctness.

You will work close to technical leadership and product teams to turn security workflows into backend systems that are fast, reliable, auditable, and maintainable.

This is not a narrow implementation role. You should be comfortable making architectural calls, writing production code, owning infrastructure, and being accountable when systems fail.

Enterprise security data is messy, high-volume, and operationally sensitive.

The platform needs to ingest and process signals from cloud environments, security tools, infrastructure systems, and customer workflows, then make that context usable by AI agents and human security teams.

The hard part is not just moving data. It is building backend systems that preserve context, support real-time workflows, handle failure cleanly, and remain reliable under enterprise constraints.

That puts pressure on event-driven architecture, cloud infrastructure, data modeling, API design, observability, permissions, latency, cost, and operational safety.

• Cloud backend architecture: design and build backend services, APIs, and data pipelines that support agentic cybersecurity workflows.
• Technical delivery: lead systems from architecture and design through implementation, testing, deployment, and operations.
• Data pipelines: build reliable ingestion and processing systems for security, cloud, and operational data.
• Infrastructure: own production cloud infrastructure using tools such as Terraform, Bicep, CDK, serverless services, databases, and event-streaming systems.
• Reliability and observability: build systems that are measurable, debuggable, and resilient under real customer usage.
• CI/CD and automation: improve deployment quality, test automation, infrastructure-as-code practices, and operational repeatability.
• Backend performance: improve latency, throughput, scalability, and cost-performance across services and pipelines.
• Cross-functional execution: work with product, design, security, and engineering teams to turn ambiguous workflows into concrete backend systems.
• Engineering standards: raise the quality bar for code, architecture, testing, documentation, and production ownership.

You are likely a strong fit if you have:

• 7 years of backend or cloud engineering experience, ideally in production systems with meaningful scale or reliability requirements.
• Strong hands-on experience with Python in production backend systems.
• Deep experience with AWS or Azure, including cloud-native architecture, infrastructure automation, databases, and event-driven systems.
• Experience with infrastructure-as-code tools such as Terraform, Bicep, or CDK.
• Strong backend fundamentals: API design, distributed systems, data modeling, async processing, testing, deployment, and operational debugging.
• Experience with cloud services such as API Gateway, Lambda, RDS, DynamoDB, Kinesis, or equivalent systems.
• Comfort working across application code, infrastructure, observability, and production operations.
• The judgment to know when to use serverless, managed services, event streams, relational databases, NoSQL stores, or custom services.
• Clear communication when requirements are incomplete, systems are failing, or tradeoffs need to be made.
• A high ownership bar: you do not stop at “code merged”; you care whether the system works in production.

Strong bonus signals:

• Experience with cybersecurity, cloud security, enterprise security tooling, or regulated enterprise software.
• Experience with Golang, Kafka, high-throughput event pipelines, or multi-cloud infrastructure.
• Experience building systems used by large enterprise customers.
• Experience in early-stage teams where senior engineers own architecture and execution directly.

• Languages: Python, Golang
• Cloud: AWS, Azure
• Infrastructure: Terraform, Bicep, CDK
• Backend and APIs: API Gateway, Lambda, backend services, internal APIs
• Databases: RDS, DynamoDB
• Streaming and pipelines: Kinesis, Kafka
• Engineering practices: CI/CD, Infrastructure as Code, observability, test automation

The stack matters, but judgment matters more. The right person can reason from first principles across cloud architecture, backend design, and operational constraints.

The company is still early enough that a senior engineer can shape core backend architecture, infrastructure standards, and production practices.

The next constraint is execution quality: turning a technically ambitious cybersecurity platform into systems that enterprise customers can rely on every day.

For someone who wants senior-level ownership without the process drag of a large company, this is a high-leverage seat.

• You want a narrow backend role with tightly scoped tickets.
• You prefer to stay far from infrastructure, deployment, and production operations.
• You are not comfortable working 5 days per week in office.
• You need mature processes, fully specified requirements, and long planning cycles.
• You do not want accountability for reliability, observability, and operational quality.
• You prefer consumer-product speed over enterprise-grade correctness.

• Base salary: $225K–$250K, based on experience and qualifications
• Bonus: $15K–$30K annual discretionary bonus
• Equity: competitive
• Location: North San Jose, CA
• Work policy: 5 days in office
• Employment: full-time
• Visa support: available case by case

• Initial screen: 30–45 minutes
• Technical interviews: remote, approximately 90 minutes
• On-site interviews: approximately 90 minutes

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