Our Benefits In The U
Technology
SeniorSoftwareEngineer
Neural analysis suggests this role is
optimal for Senior candidates.
“Senior Software Engineer at Our Benefits In The U. Skills: Data Platform, Distributed Systems, API Development, Automation. Design scalable APIs. Develop scalable APIs”
Industry & Context.
Solve hard distributed systems problems
On-call rotations
What They're Looking For.
Must Have
5+ years software engineering experience, Go, Java, or Python programming, Design and build distributed systems, Build microservices architectures, Cloud platforms experience, Build and consume APIs, CI/CD understanding, Containerization understanding, Cloud native infrastructure understanding, Learn new technologies quickly, Ownership mindset, Streaming technologies experience, Big data ecosystems experience, Build data platforms, Build storage systems, Build orchestration engines, Data modeling familiarity, Schema design familiarity, Large-scale data processing familiarity, Implement observability frameworks, Implement monitoring frameworks, Build developer platforms, Build internal tooling
Nice to Have
AWS preferred, Kafka experience, Flink experience, Spark experience, Trino/Presto experience, Hive experience, EMR experience, Airflow experience, Temporal experience
What You'll Do.
Develop scalable APIs
Develop microservices
Build backend services
Develop full-stack capabilities
Architect distributed systems
Implement distributed systems
Process millions of records
Build streaming systems
Build ingestion systems
Develop control-plane services
Design self-service infrastructure
Build highly available systems
Build fault-tolerant systems
Implement cloud-native practices
Drive performance optimization
Drive system efficiency
Participate in on-call rotations
Take operational ownership
Identify manual processes
Replace manual processes
Build intelligent workflow systems
Build orchestration systems
Build scheduling systems
Improve deployment pipelines
Reduce operational overhead
Leverage modern tooling
Partner with product managers
Partner with architects
Partner with data engineers
Partner with ML teams
Translate business needs
Contribute to architectural direction
Contribute to technical strategy
Raise engineering bar
Conduct design discussions
Promote engineering best practices
Promote documentation discipline
Promote long-term maintainability
How You'll Work.
Team & Collaboration
Partner with product managers; Partner with architects; Partner with data engineers; Partner with ML teams
Process & Methodology
CI/CD
Full Job Description
**Job Requisition ID #** 26WD97797 **Position Overview** Autodesk’s Data Platform is building the next generation of data infrastructure — AI native, scalable and developer-friendly systems that power analytics, AI, real-time insights, and customer-facing experiences across Autodesk. To power this vision, we are hiring software engineers who build platforms. You are someone who learns quickly, moves decisively, and takes ownership of complex systems. You enjoy solving hard distributed systems problems, writing production-grade code, automating everything, and turning ambiguity into scalable architecture. You will design and build APIs, streaming systems, control planes, automation frameworks, and developer-facing platform capabilities that enable thousands of engineers and data practitioners across Autodesk. This is a high-impact engineering role with real architectural ownership. **Responsibilities** * Design and develop scalable APIs and microservices (REST, GraphQL, event-driven) * Build backend services using modern languages such as **Go, Java, or Python** * Develop full-stack capabilities when needed (React, micro-frontends) to enable platform usability * Architect and implement distributed systems that process millions of records across batch and real-time pipelines * Build and evolve streaming and ingestion systems using Kafka and Flink * Develop control-plane services for orchestration, workflow management, and metadata-driven automation * Design self-service infrastructure abstractions for storage, compute, and workflow provisioning * Build highly available, fault-tolerant distributed systems * Define SLAs/SLIs and drive observability across platform services * Implement strong testing, CI/CD, and modern, cloud-native practices * Drive performance optimization and system efficiency * Participate in on-call rotations and take operational ownership seriously * Identify manual processes and replace them with resilient automation * Build intelligent workflow o
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