Sr. Software Engineer - Distributed Systems

Workday; Santa Clara (CA); Hybrid; USD 150,000 - 190,000; Full time

Job summary

Workday is hiring for a Senior/Mid-Level Software Engineer to join the Data Platform and Observability team. Hybrid work with up to 50% remote, focusing on building scalable observability services and AI-driven tools for real-time and batch data processing.

You will own tracing, instrumentation, and dashboards, collaborating across platforms and cloud environments, while shaping SLOs/SLIs and production readiness for critical services.

Qualifications

• 8+ years in software eng/design with strong Python/Go/Java background.
• Experience Linux-based environments and distributed systems.
• Strong understanding of time-series databases, log collection, and data integrity.

Responsibilities

• Design and improve observability services: Monitoring, Logging, Alerting, Tracing.
• Own end-to-end distributed tracing, context propagation, and multi-hop diagnostics.
• Build data capture/collection services across Kubernetes, Docker, OpenStack, bare metal.
• Develop core software for real-time and batch data processing.
• Create metrics pipelines, alerting rules, and dashboard tooling.
• Apply AI-driven observability techniques to reduce noise and speed incident response.
• Partner with product teams to define SLOs/SLIs and production readiness.
• Develop production infrastructure and deploy in production.

Skills

Python

Go

Java

Linux

Time-series DBs

Distributed tracing

Public cloud

Docker

Kubernetes

Ansible

Chef

Terraform

Prometheus

CloudWatch

LangChain

LlamaIndex

Semantic Kernel

LLM orchestration

Education

BS in Computer Science

MS degree (plus)

Tools

Docker

Kubernetes

Ansible

Chef

Terraform

AWS CloudWatch

GCP Stackdriver

Prometheus

Job description

Your work days are brighter here. We’re obsessed with making hard work pay off, for our people, our customers, and the world around us. As a Fortune 500 company and a leading AI platform for managing people, money, and agents, we’re shaping the future of work so teams can reach their potential and focus on what matters most. The minute you join, you’ll feel it. Not just in the products we build, but in how we show up for each other. Our culture is rooted in integrity, empathy, and shared enthusiasm. We’re in this together, tackling big challenges with bold ideas and genuine care. We look for curious minds and courageous collaborators who bring sun-drenched optimism and drive. Whether you're building smarter solutions, supporting customers, or creating a space where everyone belongs, you’ll do meaningful work with Workmates who’ve got your back. In return, we’ll give you the trust to take risks, the tools to grow, the skills to develop and the support of a company invested in you for the long haul. So, if you want to inspire a brighter work day for everyone, including yourself, you’ve found a match in Workday, and we hope to be a match for you too.

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