Backend Engineer II, Location Platforms

Summary

Yahoo is a technology company connecting its brands and partners with hundreds of millions of people through large-scale digital products and services. The Backend Engineer II will develop, test, deploy, and operate scalable location platform services, APIs, and data pipelines, while participating in reviews, on-call support, troubleshooting, and operational improvements.

Responsibilities

• Develop, test, and deploy production-ready code for location services, working on well-defined features and bug fixes within existing location APIs and data pipelines
• Implement solutions against technical designs established by senior engineers and architects, delivering with limited day-to-day guidance
• Use Yahoo-approved AI development tools (e.g., Claude Code, GitHub Copilot, or Cursor) to accelerate implementation, testing, debugging, and documentation
• Write comprehensive unit and functional tests, and refactor existing code to improve reliability, performance, and maintainability
• Troubleshoot software failures and operational issues across distributed Linux, public cloud (AWS/GCP), and on-premise Hadoop environments, conducting root-cause analysis to prevent recurrence
• Participate in an on-call rotation for services handling billions of requests daily, responding to incidents and driving follow-up fixes
• Participate actively in code reviews, design reviews, technical planning, and agile story estimation — asking clarifying questions and proactively surfacing risks
• Contribute to team metrics dashboards, documentation, and operational standards, and adhere to team coding and documentation practices

Skills

• BS or MS in Computer Science or a related technical discipline, or equivalent practical experience
• 2+ years of hands-on software development experience building scalable applications or platform services
• Proficiency in Java, with solid grounding in object-oriented design
• Working knowledge of big data systems (Spark, Hive, Hadoop) and cloud platforms such as AWS or GCP; Python or Scala for data processing at scale
• Working experience in UNIX/Linux environments
• Hands-on experience using AI-assisted development tools (e.g., Claude Code, GitHub Copilot, or Cursor) in day-to-day engineering work, and a willingness to adopt LLM-based workflows to improve engineering velocity
• Understanding of web service APIs and RESTful design
• Experience working with large datasets and batch or streaming data pipelines
• Strong oral and written communication skills, with a collaborative, customer-first approach and openness to feedback
• Experience with real-time and streaming systems (Kafka, Flink, or similar) for high-volume signal processing
• Experience building and operating containerized services on Kubernetes and Docker
• Familiarity with Infrastructure-as-Code (Terraform, Ansible) and automated CI/CD pipeline design and maintenance
• Awareness of privacy and consent requirements for handling user location data (GDPR, CCPA, or similar frameworks)
• Exposure to machine learning concepts and their application to location inference or signal quality
• Interest or experience applying AI tooling — custom prompts, agents, or automated workflows — to engineering problems such as data quality, pipeline debugging, or developer productivity
• Any exposure to geospatial or location data is a nice-to-have, not a requirement — map data, geocoding, IP geolocation, spatial indexing, POI/place data, or trajectory processing. We're glad to teach the domain to strong backend engineers

Qualifications

Must Haves

• BS or MS in Computer Science or a related technical discipline, or equivalent practical experience
• 2+ years of hands-on software development experience building scalable applications or platform services
• Proficiency in Java, with solid grounding in object-oriented design
• Working knowledge of big data systems (Spark, Hive, Hadoop) and cloud platforms such as AWS or GCP; Python or Scala for data processing at scale
• Working experience in UNIX/Linux environments
• Hands-on experience using AI-assisted development tools (e.g., Claude Code, GitHub Copilot, or Cursor) in day-to-day engineering work, and a willingness to adopt LLM-based workflows to improve engineering velocity
• Understanding of web service APIs and RESTful design
• Experience working with large datasets and batch or streaming data pipelines
• Strong oral and written communication skills, with a collaborative, customer-first approach and openness to feedback

Nice to Haves

• Experience with real-time and streaming systems (Kafka, Flink, or similar) for high-volume signal processing
• Experience building and operating containerized services on Kubernetes and Docker
• Familiarity with Infrastructure-as-Code (Terraform, Ansible) and automated CI/CD pipeline design and maintenance
• Awareness of privacy and consent requirements for handling user location data (GDPR, CCPA, or similar frameworks)
• Exposure to machine learning concepts and their application to location inference or signal quality
• Interest or experience applying AI tooling — custom prompts, agents, or automated workflows — to engineering problems such as data quality, pipeline debugging, or developer productivity
• Any exposure to geospatial or location data is a nice-to-have, not a requirement — map data, geocoding, IP geolocation, spatial indexing, POI/place data, or trajectory processing. We're glad to teach the domain to strong backend engineers

Benefits

• Flexible hybrid work options, with most roles not requiring regular office attendance
• Discretionary annual bonus or commissions
• Healthcare
• 401k
• Backup childcare
• Education stipends
• Employee resource groups (ERGs) with programs, events and fellowship that help educate, support and create a workplace where all feel welcome