Senior Software Engineer contributing to Workday's AI/MLOps cloud ops platform. Involves data ingestion, computation, and generation of curated data sets with modern technologies.
Responsibilities
Contribute to a cloud ops platform that enables ingestion of data from internal and external producers
Compute and aggregate meaningful, curated data sets
Surface these sets to Workday Front-End components or as embedded contextual data for AI/ML inference generation and agentic workflows
Utilize technologies like Kubernetes, Spark, Python, Java, XO, Terraform, Iceberg, EMR, and Sagemaker.
Requirements
6+ years of experience in Software Engineering, Distributed Systems or a related field
3+ years proficiency in at least two of the following programming languages: Java, Scala, Python
3+ years in cloud engineering or related field(s)
Working knowledge of cloud-based infrastructure and managed services (AWS, GCP)
Experience with at least one of these data engineering technologies: Apache Spark, Apache Iceberg, Kubernetes, Terraform AWS Cloud Infrastructure
BSc or MSc in Computer Science/Computer Engineering or equivalent experience
Experience in delivering a service from writing code to deploying in production: continuous integration (Jenkins), virtualisation (Docker), orchestration (Kubernetes, Terraform)
Experience utilizing AI-Code Generation tools such as ClaudeCode, Windsurf, Cursor etc
Experience creating scalable service endpoints to retrieve data
Track record of working with logging, monitoring, metrics, stats technologies, such as: Grafana, Prometheus, Kibana, Hive, etc
Proficient collaborating with teammates to design, maintain and improve sophisticated object-oriented software following clean code standard methodology; A testing/quality approach - unit, system/integration and end-to-end testing, TDD, feature toggles, and canary deployments
Exposure to operating system concepts covering memory and storage, threading and concurrency, networking and sockets, and process management
An understanding and experience with topics related to performance and scale, security, availability, deployment and operations
Experience being responsible for a service in production with experience of production triage and on-call.
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