DevOps Engineer I

Summary

The DevOps Engineer I supports the reliability, security, and delivery of cloud infrastructure and the systems that run Spring Venture Group's platforms. This is an entry-level DevOps position with defined scope, structured oversight, and a clear path to broader ownership.

The team applies a measured, controlled approach to change. Work is peer-reviewed, automated where it improves safety, and deployed in a manner that can be audited and rolled back.

About Spring Venture Group

Spring Venture Group is a leader in Medicare health insurance distribution. The company helps consumers select health coverage that fits their needs and supports them in making informed decisions about their health and financial well-being.

Customer trust depends on technology that performs consistently. The DevOps team designs, improves, and supports the cloud platforms and delivery systems on which internal and customer-facing applications are built.

Position Overview

The DevOps Engineer I designs, modernizes, and supports core cloud infrastructure and the pipelines used to deliver it. The position works with proprietary platforms and current third-party tools, including AI-assisted coding tools for research, drafting, and routine technical tasks.

Primary focus areas are system reliability, delivery pipeline quality, and a secure operating baseline. The engineer collaborates with developers and senior DevOps engineers, operates under guidance, and assumes expanded responsibility as technical experience develops.

Assignments are of limited to moderate complexity and are performed under oversight. Typical work includes improving a pipeline, implementing a backup or monitoring control, remediating a security finding, and supporting developer deployments.

*Work authorization: Spring Venture Group is unable to sponsor this position now or in the future. Candidates must be a U.S. citizen or a lawful permanent resident (green card holder).*

Representative Work

- Improve a CI/CD pipeline to increase deployment reliability for a development team.
- Convert a recurring manual check into a documented, reviewed automation.
- Reduce alert noise by refining Datadog or CloudWatch monitors.
- Close a security finding through an infrastructure change that is version-controlled and reproducible.
- Support senior engineers on CDK or CloudFormation updates to shared modules.
- Document incident findings and contribute to corrective actions.
- Use AI-assisted tools to draft scripts or summarize documentation, with results validated before use in any non-development environment.

Operating Principles

- Controlled change. Releases are kept small and reviewable. Rollback procedures are defined before deployment.
- Security by default. Least-privilege access, reviewed infrastructure code, timely remediation of findings, and no secrets in source code or chat logs.
- Automation with defined value. Manual processes are documented first, then automated where the return is clear.
- Accountability for changes . AI-assisted tools accelerate drafting and research. The engineer is accountable for all changes that are merged and deployed.
- Human review of decisions. AI tools are used extensively for data gathering and analysis. Decision points remain under human review.
- Structured development. Mentorship, code review, and oversight are part of the role, supporting progression to more complex work.

Spring Venture Group behaviors applicable to this role

- Be Aware: Emotional intelligence
- Be Open & Honest: Communication
- Be a Team Player: Teamwork and collaboration
- Be Accomplished: Drive for results
- Be the Example: Develop self and empower people
- Be Forward Thinking: Strategic thinking
- Be a Problem Solver: Continuous improvement

Responsibilities

Deliver infrastructure initiatives and engineering requests to required quality standards, applying sound technical judgment and approved AI-assisted engineering tools.; Monitor, troubleshoot, maintain, and improve automated build, packaging, and deployment processes.; Implement automated infrastructure capabilities, including backups, security scanning, and system monitoring.; Apply DevOps and Site Reliability Engineering practices to improve process quality across the change lifecycle, from code commit through production release.; Collaborate with the DevOps Manager, DevOps Team Leads, senior engineers, and software development teams. Seek guidance as needed and document technical decisions and procedures.; Implement security and vulnerability remediations identified by the DevOps team, and escalate newly identified risks promptly.; Use AI coding assistants for research, drafting, and routine tasks. All AI-generated output is reviewed, tested, and deployed through the standard reviewed pipeline.; Manage and implement company tools, solutions, and platforms, including:; CI/CD: GitHub, GitHub Actions, AWS CodeBuild, AWS CodePipeline, and related deployment tooling; Infrastructure as Code: AWS CDK and AWS CloudFormation; Observability: Datadog, Amazon CloudWatch, and OpenTelemetry; Automation: Python, Bash, Node.js, and similar scripting languages; AI assistants: Approved AI coding and analysis tools used for software development, data gathering, and analysis; Support developer teams in local and cloud environments, including containerized (Docker, Amazon EKS) and serverless workloads as applicable.; Participate in an on-call rotation to triage, troubleshoot, and resolve production issues of varying scope and complexity.; Perform other duties and responsibilities as assigned.

Requirements

Bachelor's degree in Computer Science, Computer Engineering, or a related technical field, or; One (1) year of hands-on experience in DevOps, Site Reliability Engineering (SRE), or Systems Administration roles.; Hands-on experience with Amazon Web Services (AWS).; Proficiency with continuous integration and continuous delivery (CI/CD) pipelines, infrastructure as code (IaC) tooling, and application and infrastructure hosting.; Scripting proficiency in Python, Bash, or a comparable language.; Strong troubleshooting skills and a methodical approach to root-cause analysis.; Proficiency with AI assistants for software development and engineering tasks.; Clear written and verbal communication, including status reporting and risk escalation.; Collaborative working style and receptiveness to technical feedback.

Nice to have

Experience with containerization (Docker, Kubernetes/Amazon EKS) or serverless architectures on AWS.; Familiarity with Datadog, CloudWatch, or comparable observability platforms.; Experience with vulnerability remediation or compliance-driven operations.; Experience with configuration or build tools such as Ansible or Jenkins. Useful background, current delivery is based on GitHub Actions, AWS services, and infrastructure as code.