Senior Software Engineer

Who you are

• 5+ years of professional software engineering experience building production systems
• Strong programming skills in Go, Java, or Python
• Proven experience designing and building distributed systems or microservices architectures
• Experience with cloud platforms (AWS preferred)
• Experience building and consuming APIs (REST, GraphQL, event-driven)
• Strong understanding of CI/CD, containerization, and cloud native infrastructure
• Demonstrated ability to learn new technologies quickly and apply them effectively
• Ownership mindset: you build it, you run it, you improve it
• Experience with streaming technologies (Kafka, Flink)
• Experience with big data ecosystems (Spark, Trino/Presto, Hive, EMR)
• Experience building data platforms, storage systems, or orchestration engines (Airflow, Temporal)
• Familiarity with data modeling, schema design, and large-scale data processing
• Experience implementing observability and monitoring frameworks
• Background in building developer platforms or internal tooling

What the job involves

• 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
• 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 orchestration and scheduling systems
• Improve deployment pipelines and reduce operational overhead
• Leverage AI/LLMs and modern tooling to accelerate engineering productivity
• Partner with product managers, architects, data engineers, and ML teams to translate business needs into scalable systems
• Contribute to architectural direction and technical strategy
• Mentor engineers and raise the engineering bar through code reviews and design discussions
• Promote engineering best practices, documentation discipline, and long-term maintainability
• This role may require in-person onboarding and/or in-person ID verification