Production Engineer

WebMD is the most recognized and trusted brand of health information and the leading provider of health information services, serving consumers, physicians, healthcare professionals, employers and health plans through our public and private online portals and WebMD the Magazine. The WebMD Health Network includes WebMD, Medscape, Medicine Net, eMedicine, RxList, theheart.org and Medscape Education. Our consumer portals and mobile health applications provide engaging, relevant and credible health and wellness information, personalized health assessment tools and access to online communities.

WebMD is an Equal Opportunity/Affirmative Action employer and does not discriminate on the basis of race, ancestry, color, religion, sex, gender, age, marital status, sexual orientation, gender identity, national origin, medical condition, disability, veterans status, or any other basis protected by law.

As a Production Engineer, you’ll join WebMD’s SRE team to manage, improve, and evolve our entire backend stack. In this role, you will focus heavily on maintaining our Windows-based infrastructure as well as Linux and Kubernetes.

• Manage and optimize our Windows Server environments and Kubernetes clusters to ensure the high availability and reliability of WebMD’s popular sites and services.
• Automate tasks and routines through modern scripting (primarily Power Shell and Python), simplifying developer and operations workflows.
• Take ownership of tasks and projects within our Observability stack (including Prometheus and ELK) to maintain full-stack visibility, latency tracking, and scalability.
• Identify opportunities for infrastructure improvement, collaborate with other Operations teams, and act as a driver of change.

• Demonstrate fluency in working with Windows Server operating systems
  , paired with a strong command-line aptitude and a willingness to learn or work within Linux environments
  .
• Show hands-on proficiency in deploying, managing, or troubleshooting workloads within Kubernetes
  .
• Provide samples of automation scripts built using Power Shell
  , Python, or Go.
• Leverage AI-assisted engineering tools (such as Git Hub Copilot, Claude Code, or LLMs) to accelerate scripting, troubleshooting, and daily operational workflows.
• Drive continuous improvement within our Observability and monitoring ecosystems (Prometheus, Grafana, ELK Stack).
• Demonstrate operational competency with critical stack technologies:
  • Configuration management (e.g., Puppet, Ansible)
  • Load balancers (specifically F5 Big-IP
    )
  • Data and messaging layers (e.g., Redis, Kafka, RabbitMQ)
  • Convey a fundamental understanding of CI/CD pipelines (Git Lab, Jenkins, or Azure Dev Ops).
• Participate in the team’s on-call rotation to address production issues outside of working hours.

• Bachelor's degree in Computer Science, Technology, Engineering, Math, or equivalent practical experience.
• 4+ years of overall experience in IT/Infrastructure, with 2+ years of relevant experience supporting web-based applications for large-scale, high-traffic websites.
• Proven experience troubleshooting and performance tuning distributed systems, IIS, and web applications.
• Fundamental understanding of network concepts (TCP/IP, DNS, HTTP) and traffic management via F5 Big-IP
  .
• An open, adaptive mindset toward adopting new methodologies, whether that means jumping into a Linux CLI or integrating AI tools into your daily engineering workflow.
• Excellent communication skills, with the ability to convey detailed technical concepts clearly to both peers and non-technical stakeholders.

This position is also eligible for a discretionary company bonus, based upon business results.

$109,000 - $120,000

• Health Insurance (medical, dental, and vision coverage)
• Paid Time Off (including vacation, sick leave, and flexible holiday days)
• 401(k) Retirement Plan with employer matching
• Life and Disability Insurance
• Employee Assistance Program (EAP)
• Commuter and/or Transit Benefits (if applicable)

Eligibility for specific benefits may vary based on job classification, schedule (e.g., full-time vs. part-time), work location and length of employment.