Origami Risk LLC
• $100K — $122K *Qualifications
Responsibilities
Benefits
A great platform team is defined not by how many tickets it closes, but by how little friction stands between an engineer's idea and a running service. The DevOps Engineer, Platform builds and runs the pipelines, golden paths, service infrastructure, and AI-augmented workflows that make delivery self-service at Origami Risk.
This engineer is a hands-on member of the DevOps Platform team who onboards new services, builds and maintains CI/CD pipelines, authors infrastructure as code, deploys and operates containerized and serverless workloads, and keeps the path from lower environments to production reliable. Everything runs in AWS, on top of the landing zone the DevOps Infrastructure team owns. The role works from the team's established standards and patterns, contributes improvements back to them, and partners with Engineering, Release, SRE, and DevOps Infrastructure to deliver services and resolve delivery issues. On this team, manual work is a problem to be solved, automation is the default, and every Engineer is expected to use AI to work faster and diagnose more accurately, while understanding and owning every change they ship.
Starting base pay for this role is between $100,000 and $122,000. The actual base pay is dependent upon many factors, such as transferable skills, work experience, business needs, training, location, and market demands. The base pay range is subject to change and may be modified in the future. This role will be eligible for a bonus as well as competitive medical, dental, and vision benefits, wellness reimbursement, life insurance, and a 401(k) with company match. We offer vacation and sick leave benefits (under a flexible time off policy in most states).
Responsibilities
What This Team Runs:
This is the developer platform and delivery layer that sits on top of the AWS landing zone: the systems Engineering uses to build, ship, and operate services every day. The team owns the platform for application and service delivery, not the landing zone underneath it, which the DevOps Infrastructure team owns. The team owns:
• Delivery Pipelines & Build: the CI/CD build and deploy pipelines, and the shared pipeline templates that Engineering teams across the org use to ship every day.
• Service-Layer IaC: the infrastructure-as-code that defines each service's cloud resources, versioned and deployed through Terraform.
• Kubernetes & Container Platform: the Kubernetes container platform and the self-service golden path that lets a new service onboard with no bespoke infrastructure work.
• Application Connectivity: the application-facing API gateways, service DNS, and certificates that make services reachable and secure.
• Service Data & Configuration: the application data stores, configuration, and secrets that each service depends on.
• Environment Promotion: the promotion path that moves a change safely from lower environments to production.
• AI & Internal Tooling: the AI tooling across the development lifecycle that speeds service onboarding, pipeline authoring, and day-to-day delivery.
Key Responsibilities:
Developer Platform & Service Onboarding
• Onboards new services and greenfield projects through the team's self-service golden path, from repository scaffolding and infrastructure provisioning through pipelines, configuration, secrets, DNS, and alerting, taking each service from “we are building a service” to “it deploys to production on its own pipeline.”
• Supports high-velocity delivery for new product initiatives, including AI projects, by enabling Day-1 deployment from initial repo creation through infrastructure provisioning, application deployment, observability, and production readiness.
• Applies the team's naming and structural standards for repositories, container images, pipelines, configuration, and secrets, and flags gaps where a standard is missing or unclear.
• Supports cost efficiency by right-sizing service infrastructure, applying image and artifact retention policies, and cleaning up idle or unused resources.
Pipelines, Build & Release
• Builds, maintains, and troubleshoots CI/CD build and deploy pipelines (build, test, scan, containerize, publish, deploy, and the environment gates between them) using the team's shared pipeline templates.
• Contributes changes to shared pipeline templates in a backward-compatible way, so new options carry safe defaults and existing consumers never break.
• Maintains container image discipline, including immutable versioning, registry management, and retention policies, so a redeploy always runs exactly the image that was tested.
• Executes promotions from lower environments to production through gated, repeatable pipelines, with roll-forward as the default recovery path.
• Supports the Release team in operating the pipelines DevOps builds, helping them read a failure, retry or approve a stage, and know when to escalate back to DevOps versus the service owner.
• Investigates flaky and intermittent pipeline failures to their root cause rather than retrying past them.
• Manages change requests and work items within defined SLAs, including change-advisory and release coordination for production promotions.
Service IaC & Container Platform
• Authors and maintains infrastructure as code in Terraform for each service's cloud resources, including compute, serverless functions, API gateways, load balancers, storage, configuration, alarms, and workload IAM roles, with every change versioned, peer-reviewed, and deployed through automation.
• Treats manual changes as exceptions to be codified promptly, using plan output and state analysis to detect and resolve configuration drift.
• Deploys and operates containerized and serverless workloads on Kubernetes and managed container services, including Helm-based releases, namespaces, workload identity, and network policies.
• Configures application connectivity, including API gateways, request authorizers, service DNS records, and TLS certificates, and debugs request-path failures end to end.
• Provisions the data stores, configuration, and secrets that belong to a service, including managed relational databases with automated schema-migration pipelines, handing ongoing database operations to the Database team.
AI-Augmented DevOps
• Uses AI development tools in daily work for infrastructure code, pipeline authoring, automation scripting, troubleshooting, and documentation, while reviewing, testing, and owning everything AI produces.
• Contributes to the team's internal AI tooling across the software development lifecycle and shares effective prompts, patterns, and workflows with the team.
Service Observability & Incident Response
• Wires services into logging, metrics, and tracing as part of each service's infrastructure code, including retention and log-volume controls, and confirms a new or promoted service emits telemetry before it is handed to SRE.
• Identifies, diagnoses, and resolves delivery and service issues in production and pre-production, including failed deploys, connectivity faults, container and runtime configuration problems, and configuration drift, using observability platforms, cluster tooling, pipeline logs, and infrastructure state.
• Recognizes quickly when an issue belongs to another team and hands it off with evidence.
Security, Compliance & Access
• Implements the security controls the team owns within the delivery path, including least-privilege workload roles scoped to a single service, secrets management, container and pipeline security scanning, and network-policy enforcement, operating within the guardrails DevOps Infrastructure sets.
• Keeps pipeline and platform access least-privilege, including service connections, federated cloud credentials, and repository and pipeline permissions, and supports audit evidence collection for SOC 2, ISO/IEC 27001, and NIST 800-53.
Collaboration & Documentation
• Partners with Engineering teams during onboarding and system design so that services are operationally sound and reliably deployable.
• Coordinates with cross-functional teams on shared boundaries so that requests do not stall between teams.
• Works intake and sprint commitments in the team's work-tracking system, keeping work items current, estimated, and visible.
• Creates and maintains technical documentation, including infrastructure READMEs, deployment runbooks, service onboarding guides, troubleshooting notes, and project status updates.
Qualifications
• Bachelor's Degree in Computer Science or related field, or commensurate on-the-job experience
• 3+ years of experience in a DevOps, platform, infrastructure, or software engineering role supporting production systems in AWS
• Hands-on experience with AWS services for application delivery, such as container and serverless compute, API gateways, load balancers, object storage, managed databases, IAM, DNS, and secrets and configuration management
• Experience writing and maintaining Terraform in a team setting, including modules, remote state, plan review, and drift resolution
• Experience building and troubleshooting CI/CD pipelines in a platform such as Azure DevOps, GitHub Actions, or GitLab CI, including reusable templates and environment-gated deployments
• Experience with Docker, container registries, and running containers on Kubernetes or managed container services
• Ability to code and script in Python, PowerShell, or Bash with an emphasis on testing, automation, and reliable deployments; familiarity with configuration management tools
• Working knowledge of building and deploying backend services and modern web front ends (e.g., .NET, Java, Node.js, React)
• Experience instrumenting services with logs, metrics, and traces in an observability or APM platform, and using that telemetry to troubleshoot
• Working knowledge of the networking that application delivery depends on, including DNS, TLS certificates, load balancers, and API gateways
• Strong understanding of Git, pull-request review, continuous integration, continuous deployment, environment promotion, and release automation
• Experience supporting both Windows and Linux workloads
• Regular use of AI development tools and coding assistants, with the judgment to verify and explain what the AI produces
• Familiarity with software engineering practices such as test-driven design, dependency injection, DRY principles, rapid prototyping, and service-oriented architecture
• Strong problem-solving skills, troubleshooting ability, and attention to detail, with clear written and verbal communication
Preferred Qualifications:
• AWS certification at the associate level
• Kubernetes experience with Helm and workload identity patterns
• Experience with GitOps deployment tooling
• Experience with database schema-migration tooling and relational databases
• Experience with log search and analytics platforms
• Experience with web servers and reverse proxies
• Prior experience supporting client product implementations and production rollouts
• Familiarity with SOC 2, NIST 800-53, or ISO/IEC 27001 control evidence
Benefits
Our team will look into this right away.
