About the Team
The Data Platform and Observability team is based in Pleasanton, CA; Boston, MA; and Dublin, Ireland. We enable real-time insight across Workday's platforms, infrastructure, and applications — including the AI agents and automated workflows that are becoming part of how those applications run. Our focus is building a large-scale distributed data and observability platform that keeps critical Workday services, and the AI-powered capabilities layered on top of them, fast, reliable, and trustworthy in production.
We handle hundreds of terabytes of data and billions of messages produced daily across Workday's applications and underlying services, powering a platform that tracks over 2 billion time-series in production. We're also modernizing how we do observability itself — bringing AI-driven approaches like anomaly detection, intelligent alerting, and automated root-cause analysis into the platform, so our systems get smarter about surfacing problems before they become incidents. If you enjoy writing efficient software, tuning and scaling large distributed systems, and applying AI to make observability itself sharper, you'll enjoy working with us.
Do you want to solve interesting challenges at massive scale, across private and public cloud, for 4,000+ global customers — while helping define what "observability" means for the next generation of AI-driven products? Do you want to work alongside world-class engineers building the platforms that make that possible?
If so, we should talk.
About the Role
The Data Platform and Observability team is hiring a Senior or Mid-Level Software Engineer. We have a hybrid schedule — you'll collaborate with Workmates in the office while having the flexibility to work up to 50% remote.
- Design, build, and improve critical observability services: Monitoring, Logging, Alerting, and Tracing.
- Own distributed tracing end to end — instrumenting services, propagating context across service boundaries, and using trace data to understand system behavior and diagnose issues in complex, multi-hop request paths.
- Build data capture and collection services using the latest technologies across multiple infrastructure types (Kubernetes, Docker, OpenStack, bare metal, etc.).
- Design and develop core software modules for real-time and batch data processing.
- Build metrics ingestion pipelines, alert definitions, and automation for dashboard lifecycle management.
- Instrument AI-powered and automated workflows for performance, cost, and quality, including multi-step processes and tool/service orchestration.
- Explore and apply AI-driven observability techniques — anomaly detection, intelligent alerting, and automated root-cause analysis — to reduce noise and speed up incident response.
- Partner with product and application teams to define SLOs/SLIs and production-readiness criteria for new services and automated workflows.
- Build infrastructure components and deploy them in production.
- Work across all aspects of observability with a keen eye for data quality, data integrity, and data availability.
- Evaluate and implement new open-source and cloud-native tools and technologies as needed.
- Participate in the on-call rotation supporting the observability platform.
About You
Basic Qualifications — Sr Software Engineer:
- 8 years of software engineering/design experience.
- 7 years of coding in Python, Go, or Java.
- Experience with Linux.
- BS in Computer Science or a related technical field, or equivalent experience.
Other Qualifications:
- Ability to design, maintain, and optimize Time-Series DBs, document stores, and log collection/management systems.
- Solid understanding of distributed tracing concepts (context propagation, spans, sampling) and hands-on experience with tracing tooling.
- Public cloud experience (AWS/GCP), including native observability tooling such as AWS CloudWatch and GCP Cloud Operations (Stackdriver).
- Experience with containerization and infrastructure automation (Docker, Kubernetes, Ansible, Chef, Terraform).
- Experience with service mesh, Prometheus, and cloud-native technologies.
- Hands-on experience with LLM orchestration frameworks (e.g., LangChain, LlamaIndex, Semantic Kernel) and a working knowledge of agentic AI build patterns — how agents plan, call tools, hold state, and hand off work across multi-step chains.
- A knack for spotting where AI systems quietly go wrong in production: a model call that's suddenly slower than usual, a token bill creeping up for no clear reason, or answers that subtly drift in quality over time. You know how to build the dashboards, alerts, and instrumentation that catch these early — turning "the AI feels off" into a measurable, debuggable signal.
- Excellent interpersonal, technical, and communication skills.
- Ability to prioritize multiple tasks in a fast-paced environment.
- MS Degree a plus.
Workday Pay Transparency Statement
The annualized base salary ranges for the primary location and any additional locations are listed below. Workday pay ranges vary based on work location. As a part of the total compensation package, this role may be eligible for the Workday Bonus Plan or a role-specific commission/bonus, as well as annual refresh stock grants. Recruiters can share more detail during the hiring process. Each candidate’s compensation offer will be based on multiple factors including, but not limited to, geography, experience, skills, job duties, and business need, among other things. For more information regarding Workday’s comprehensive benefits, please .
Primary Location: USA.CA.Santa ClaraPrimary Location Base Pay Range: $190,100 USD - $285,100 USD
Additional US Location(s) Base Pay Range: $160,100 USD - $285,100 USD
Additional Considerations:
If performed in Colorado, the pay range for this job is $168,500 - $252,700 USD based on min and max pay range for that role if performed in CO.
The application deadline for this role is the same as the posting end date stated as below:
11/30/2026
Our Approach to Flexible Work
With Flex Work, we’re combining the best of both worlds: in-person time and remote. Our approach enables our teams to deepen connections, maintain a strong community, and do their best work. We know that flexibility can take shape in many ways, so rather than a number of required days in-office each week, we simply spend at least half (50%) of our time each quarter in the office or in the field with our customers, prospects, and partners (depending on role). This means you'll have the freedom to create a flexible schedule that caters to your business, team, and personal needs, while being intentional to make the most of time spent together. Those in our remote "home office" roles also have the opportunity to come together in our offices for important moments that matter.
