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Fannie Mae

Buys home loans from lenders and guarantees them

Lead Platform Automation Engineer

Platform EngineeringConfirmed live in the last 24 hours
Full-time

About the Job

Requirements

  • At least 4 years of experience.
  • Strong software development experience with modern programming languages such as Python, Java, and Node.js, and frameworks, with demonstrated ability to design, develop, test, and support scalable production solutions.
  • Hands-on experience designing, developing, and deploying cloud-native solutions on AWS, using services such as ECS, EKS, AWS Lambda, S3, SNS, SQS, and Step Functions.
  • Experience designing and developing workflow automation and orchestration solutions using technologies such as Temporal or similar workflow orchestration platforms.
  • Experience designing, developing, and integrating REST APIs and API-based services across enterprise platforms and technology ecosystems.
  • Experience with platform engineering, CI/CD, Git-based development, and automation practices, including building reusable engineering frameworks, harnesses, and workflow components.
  • Experience using AI-assisted software development tools such as GitHub Copilot, Claude, ChatGPT, or similar technologies to support software development, workflow automation, testing, troubleshooting, and engineering productivity.
  • Experience implementing and supporting monitoring, logging, metrics, tracing, and observability solutions to assess application and platform health, troubleshoot failures, and improve operational reliability.
  • Demonstrated experience troubleshooting complex distributed systems, platform integrations, and production issues, including root-cause analysis, incident resolution, resiliency, and continuous improvement.
  • Show curiosity and adaptability in learning and responsibly applying new technologies, including artificial intelligence, to reimagine how work is done.

Responsibilities

  • Design, develop, and support automated workflows using modern workflow orchestration technologies, including Temporal, to streamline complex, multi-step provisioning and platform processes.
  • Integrate AI-assisted development capabilities into platform engineering workflows to improve developer productivity, reduce repetitive engineering activities, and accelerate delivery of automation solutions.
  • Use GitHub Copilot, Claude, ChatGPT, and other AI-assisted development tools to accelerate workflow development, code generation, refactoring, troubleshooting, documentation, and test automation.
  • Design, implement, and maintain unified observability solutions to monitor build volumes, success and failure rates, component versions, runtime impact, and other key operational metrics.
  • Monitor and troubleshoot complex platform, workflow, integration, and application issues, identifying root causes and implementing solutions to improve platform reliability and operational efficiency.
  • Partner with application development teams to understand operational requirements, identify automation opportunities, eliminate manual activities, and continuously improve the developer experience.
  • Participate in technical discussions, knowledge-sharing sessions, code and design reviews, and continuous improvement initiatives across the Platform Engineering organization.
  • Support the reliability and availability of platform services through effective monitoring, troubleshooting, and collaboration with engineering and support teams.
  • Act as the team lead in designing and developing advanced solutions for IT infrastructure environments, including coding, testing, and certifying technology platforms, software, and applications, and coach and mentor team members.

Desired Qualifications

  • Bachelor’s degree in computer science or equivalent experience.
  • Relevant industry certifications such as AWS Certified Solutions Architect, AWS Certified Developer, AWS Certified DevOps Engineer – Professional, HashiCorp Terraform Associate, or comparable cloud/platform engineering certifications.
  • Hands-on experience with Temporal, Backstage, GitLab, Terraform Enterprise, and Jira in an enterprise platform engineering environment.
  • Experience with observability and telemetry standards and tools such as OpenTelemetry, Grafana, Prometheus, Splunk, Datadog, or Dynatrace.
  • Experience with AI and agent engineering concepts and frameworks, including tool calling, structured outputs, context engineering, evaluation frameworks, Model Context Protocol (MCP), or similar technologies.
  • Experience with cloud-native technologies, containers, Kubernetes, infrastructure automation, and enterprise platform engineering environments.

About the Company

Fannie Mae

Buys home loans from lenders and guarantees them

Fannie Mae buys single-family and multifamily mortgages from banks, credit unions and other lenders across the United States, giving those lenders cash to make more home loans. It does not lend to homebuyers directly; instead it pools most of the loans it buys into mortgage-backed securities and guarantees investors timely payment of principal and interest. Lenders deliver loans that meet its underwriting standards, often checked through its Desktop Underwriter system. The company earns guaranty fees on the securities it backs and interest income on loans held in its portfolio. Congress chartered it in 1938, it has operated under federal conservatorship since 2008, and it is headquartered in Washington, D.C.

Company size
5,001-10,000
Company stage
IPO
Headquarters
Washington, DC
Founded
1938

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