I
ID.me
Software Engineer (Data Platform)
Skills
Google Cloud PlatformDockerRubyPythonGolangJavaGrafanaAIAWSAnsiblePrometheusKubernetesNo-code AutomationsComplianceJavascriptTerraformAzure
2 months ago
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Important information
Contract type:
Permanent
Salary:
$172,528 – $201,375 / year
Location:
Mountain View, CA, USA
Work mode:
Onsite
Published on:
9 August 2026
What they need
- We are seeking a Site Reliability Engineer to join our Core Platform Engineering organization. The SRE team builds the automation, observability, and operational foundations that ensure ID.me’s services are reliable, scalable, and secure
- As an SRE, you will play a pivotal role in building the platform and governance processes required to safely scale, deploy, and operate a high volume of machine-generated applications and features. You will design and implement the automated guardrails that maintain our high standards for resilience and security in an AI-accelerated development environment
- You’ll focus on infrastructure automation, observability, performance optimization, and incident response, partnering closely with Software Engineering teams to foster a culture of reliability and operational excellence
- Build and maintain automated reliability tooling, infrastructure as code, and observability systems that enhance uptime and service performance
- Develop monitoring, logging, and alerting frameworks (e.g., Prometheus, Grafana, OpenTelemetry) to detect and remediate issues proactively
- Implement automated architectural reviews and reliability guardrails for agent-developed applications to ensure machine-generated code meets long-term maintainability and performance standards
- Partner with engineering teams to design and implement scalable, fault-tolerant systems that meet defined SLIs and SLOs
- Automate repetitive operational tasks and develop self-healing and auto-remediation mechanisms to minimize human intervention
- Participate in on-call rotations and lead incident response efforts, performing post-incident reviews and driving systemic improvements
- Improve the deployment and release process using CI/CD pipelines and progressive delivery techniques to ensure stability and safety
- Champion observability, reliability, and operational readiness reviews as part of the development process
- Collaborate with Security and Compliance teams to ensure production systems meet FedRAMP, NIST, and internal policy requirements
- Contribute to documentation, runbooks, and internal tooling to enhance knowledge sharing and operational maturity across teams
Benefits
- Company-Sponsored Medical, Dental, and Vision Plans for You and Your Family
- Paid Parental Leave
- Generous Paid Time Off
- 401K With Employer Matching
- Company-Sponsored Life Insurance
- Employee Equity Incentive Plan
- Remote Opportunities
- Multiple Lounge Areas and Game Room
- Numerous Mental Health Resources- 2+ years of hands-on experience managing and scaling services in cloud environments such as AWS, GCP, or Azure
- 1+ years proficiency in at least one modern programming language (e.g., Java, Go, Python, Ruby, JavaScript)
- 3-5 years of experience in Site Reliability Engineering, DevOps, or Infrastructure Engineering
- Bachelor’s degree in Computer Science, Software Engineering, or a related technical field
- Strong understanding of containerization and orchestration technologies (Docker, Kubernetes)
- Experience implementing and maintaining CI/CD pipelines and automation frameworks
- Working knowledge of observability systems—metrics, tracing, logging, and alerting
- Familiarity with event-driven architecture and asynchronous processing systems
- Experience building automated recovery, failover, or chaos-engineering systems to validate reliability
- Exposure to infrastructure-as-code tools (Terraform, Pulumi, Ansible) and GitOps practices
- Knowledge of distributed systems design, load balancing, and performance optimization
- Understanding of security and compliance frameworks (FedRAMP, SOC2, or NIST 800-53)
- Excellent communication and documentation skills, with a focus on cross-team collaboration and continuous improvement
- Strong analytical and troubleshooting skills across the stack—from network to application layer
- Experience using AI agentic coding assistants and deploying custom AI agents or automated workflows into production environments
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