A Day in the Life

We're looking for a Senior Staff DevOps Engineer to serve as a senior individual-contributor technical leader on our Platform Engineering & Operations team and scale the infrastructure underneath Lendistry's lending platform. You'll drive cloud architecture, security posture, and developer experience across a regulated financial services environment - setting technical direction and mentoring engineers so we can grow without compromising reliability or compliance.

What You'll Be Doing

Technical Leadership & Mentorship

• Serve as a senior technical leader and hands-on individual contributor for the Platform Engineering & Operations team, without formal people-management responsibilities.

• Mentor cloud and platform engineers, sharing expertise and raising the technical bar across the team.
• Contribute to and help shape the technical strategy and roadmap for infrastructure and platform engineering.

Cloud Architecture & Infrastructure

• Drive cloud architecture and account strategy across development, staging, and production environments for a regulated lending platform.
• Drive adoption of infrastructure-as-code and GitOps practices across infrastructure operations.
• Own container orchestration across multiple deployable services and cloud accounts.
• Experience with CDN/edge/WAF platforms (e.g., Cloudflare, Akamai) for content delivery, DDoS protection, edge security, and traffic/performance optimization.

Security, Identity & Compliance

• Own identity management, account-level security posture, secrets management, and KMS key strategy.
• Partner with security and compliance teams on audits and vendor/security assessments for a regulated financial services platform.

Developer Experience & CI/CD

• Own and evolve CI/CD pipelines across multiple repositories, from build through environment-gated production deployments.
• Drive best-in-class developer experience and internal tooling for engineering teams.

Reliability & Incident Management

• Contribute to on-call and incident-response practices, including postmortems, for a platform where downtime directly impacts loan funding and servicing.

AI-Native Platform Engineering

• Evaluate and drive adoption of AI-assisted engineering tools (e.g., Claude Code, GitHub Copilot) across infrastructure workflows, CI/CD pipelines, and internal tooling to accelerate delivery.
• Lead the integration of AI-driven observability and operations practices - anomaly detection, predictive alerting, and AI-assisted root-cause analysis - layered on top of existing monitoring stacks.
• Own the infrastructure strategy for ML/AI-driven product features (e.g., underwriting and fraud models), including model serving, inference monitoring, and compute scaling for AI workloads.
• Champion a builder's mindset toward internal developer platforms - self-service tooling and golden paths that let engineers ship safely without waiting on the platform team.

Your Areas of Knowledge and Expertise

• Bachelor's degree in computer science or a related discipline, or equivalent experience.
• 4+ years of experience engineering highly available, enterprise-grade software and platform applications.
• 2+ years of hands-on experience in platform engineering across various cloud computing models.
• 2+ years of hands-on experience with Kubernetes, container orchestration, Docker, and cloud-native applications.
• Substantial hands-on experience with public cloud platform services such as AWS, Azure, and GCP.
• Hands-on coding experience in at least two programming languages (Java, JavaScript, Python, Go, or .NET/C#).
• Experience with cloud-native application patterns and tools, microservices architectures, and application migrations to any cloud platform.
• Working understanding of infrastructure, virtualization, containers, networking, storage, and monitoring and logging/analytics tools (e.g., Splunk).
• Experience with application performance management tools (Splunk, AppDynamics, New Relic, Dynatrace, etc.).
• Experience with continuous integration and continuous delivery (CI/CD) tools and processes (e.g., GitHub Actions, Jenkins, Ansible).
• Experience with developer tools and open-source technologies.
• Working familiarity with MLOps/LLMOps concepts and the infrastructure needs of AI/ML workloads (GPU or accelerator provisioning, model serving, inference cost and latency management).
• Hands-on use of AI coding assistants and developer tools (e.g., Claude Code, GitHub Copilot) in real engineering workflows.
• Familiarity with policy-as-code (e.g., OPA, Kyverno) and software supply chain security practices (SBOM generation, artifact signing/provenance) as applied to CI/CD pipelines.

Preferred Expertise

• Bachelor's degree in computer science or a related discipline, or equivalent experience.
• 8+ years of experience engineering highly available, enterprise-grade software and platform applications.
• 5+ years of hands-on experience in platform engineering across various cloud computing models.
• 5+ years of hands-on experience with Kubernetes, container orchestration, Docker, and cloud-native applications.
• Substantial hands-on experience with public cloud platform services such as AWS, Azure, and GCP.
• Hands-on coding experience in at least two programming languages (Java, JavaScript, Python, Go, or .NET/C#).
• Experience with cloud-native application patterns and tools, microservices architectures, and application migrations to any cloud platform.
• Strong understanding of infrastructure, virtualization, containers, networking, storage, and monitoring and logging/analytics tools (e.g., Splunk).
• Experience with application performance management tools (Splunk, AppDynamics, New Relic, Dynatrace, etc.).
• Deep expertise in continuous integration and continuous delivery (CI/CD) tools and processes (e.g., GitHub Actions, Jenkins, Ansible).
• Extensive experience with developer tools and open-source technologies.
• Deep familiarity with MLOps/LLMOps concepts and the infrastructure needs of AI/ML workloads (GPU or accelerator provisioning, model serving, inference cost and latency management).
• Extensive hands-on use of AI coding assistants and agentic developer tools in real engineering workflows, with the judgment to evaluate where they create leverage vs. risk.
• Experience with policy-as-code (e.g., OPA, Kyverno) and software supply chain security practices (SBOM generation, artifact signing/provenance) as applied to CI/CD pipelines.

Why You'll Love Working Here:

• Comprehensive Medical, Dental, and Vision Insurance
• Generous Paid Time Off
• Birthday Day Off
• 12 Paid Company Holidays
• 401(k) Match
• FSA and HSA
• Paid Life Insurance
• Paid Disability Insurance
• Pet Insurance
• Employee Assistance Program (EAP)
• Professional Development Courses
• In Office Provided Snacks and Drinks
• Gym Facilities (LA & Tustin/CEC Offices)
• In Office Engagement Activities

Compensation Range

The US base salary range for this full-time position is $179,300 - $209,100 annually.

Our salary ranges are determined by role, level, and location.

The range displayed on each job posting reflects the minimum and maximum base salary for new hires for the position across all US locations. Within the range, individual pay is determined by multiple factors like job-related skills, experience, and state of residence. Your recruiter can share more about the specific salary range during the interview process.

Please note that the compensation details listed in US role postings reflect the base salary only, and do not include any variable compensation elements.

Physical Requirements

This is a stationary position that requires frequent sitting (approximately 95%), repetitive wrist motions, grasping, speaking, listening, close vision, and the ability to adjust focus. It also may require occasional standing, lifting, carrying of 20lbs or less, walking, kneeling, bending/stooping, twisting, pulling/pushing, and reaching above the shoulder. Employees in this position must be physically able to efficiently perform the essential functions of the position.