Job Requisition ID #26WD97363
Position Overview We are seeking a Principal Software Engineer - Backend to join Autodesk's Enterprise Data Management (EDM) organization within the COO-GET Engineering group. This is a senior individual contributor role operating at the Principal (P4) level, expected to drive technology direction for large, complex, and business-critical backend and distributed systems.
This role is anchored in backend software engineering excellence: designing, building, and evolving scalable services, APIs, and event-driven systems that operate at enterprise scale. As a Principal Engineer, you will work with high autonomy and ambiguity, shape long-term architecture, and influence multiple teams and domains. Familiarity with data engineering concepts is valuable, but backend systems, service design, and distributed systems are the core competencies.
You will function as a technical authority and force multiplier-guiding design decisions, setting standards, and ensuring Autodesk's core data services are reliable, resilient, and evolvable over time.
Responsibilities- Provide principal-level technical leadership across multiple backend and platform teams, shaping architecture and technical strategy beyond a single squad or service
- Author and evolve critical backend systems and APIs, ensuring they meet long-term scalability, reliability, and extensibility goals
- Lead design of distributed, event-driven systems, addressing consistency, ordering, failure handling, replay, idempotency, rate limiting, and backpressure
- Establish and drive service and API standards across domains, including schema design, versioning strategies, backward compatibility, and consumer experience
- Act as a technical decision-maker for cross-team initiatives; evaluate tradeoffs and make durable architectural choices aligned with business priorities
- Drive operational excellence across systems you influence: observability, alerting strategy, incident response, post-incident learning, and systemic remediation
- Introduce and reinforce engineering best practices for design reviews, code quality, testing, CI/CD, and production readiness across multiple teams
- Mentor senior engineers and emerging technical leaders; raise the bar through influence, example, and coaching rather than direct management
- Partner deeply with product, data, and platform leaders to translate ambiguous business problems into clear, actionable technical solutions
- Remain hands-on where impact is highest: complex system design, critical implementations, architectural refactors, and high-severity incident resolution
Minimum Qualifications - Bachelor's or Master's degree in Computer Science, a related technical field, or equivalent practical experience
- 10+ years of professional software engineering experience, with significant depth in backend and distributed systems
- Demonstrated expertise building and operating backend services and APIs in production environments at scale
- Strong experience with distributed systems design, including asynchronous processing, messaging, eventual consistency, and fault tolerance
- Deep hands-on experience with AWS and cloud-native architectures (compute, storage, messaging, IAM, observability, scaling patterns)
- Proven ownership of mission-critical systems, including design accountability, operational responsibility, and long-term maintainability
- Strong software engineering fundamentals: system design, service-level data modeling, API design, automated testing, CI/CD, and infrastructure as code
- Track record of influencing architecture and engineering outcomes across multiple teams without formal authority
- Excellent written and verbal communication skills, with the ability to clearly articulate complex technical concepts to diverse audiences
Preferred Qualifications - Experience building enterprise platform services consumed by many internal and/or external teams
- Familiarity with data engineering or data platform ecosystems (e.g., streaming pipelines, data warehouses such as Snowflake) as a producer or advanced consumer of data services
- Experience with event streaming and messaging platforms (e.g., Kafka, Kinesis, or equivalents)
- Background in domains such as master data management, identity resolution, data enrichment, or data quality
- Experience integrating backend services with analytics, search/indexing, or ML/AI platforms
- Prior experience operating in large, complex organizations where systems span multiple teams, regions, and business units
