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# Software Development Engineer

- **Company:** BINGHAMTOM UNIVERSITY
- **Location:** United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Agile Methodology, Artificial Intelligence, Programming Tools, Junit, Scrum Methodology, Testng, Autoscaling, Prompt Engineering, Spring-boot, Caching, Machine Learning Operations, Autodesk Autocad, Docker, Jenkins
- **Published:** June 12, 2026
- **Apply:** https://careertools.binghamton.edu/jobs/autodesk-senior-software-development-engineer-8/

## About the Role

* 10+ years of professional software engineering experience with a track record of delivering complex backend systems
 * Strong proficiency in Java (JDK 17+), and demonstrable experience working in large, multi-module Java codebases
 * Deep hands-on experience with Gradle (multi-module builds) and build system design
 * Proven, practical experience owning health, reliability and performance of CI systems and pipelines (Jenkins Declarative/Scripted pipelines, agent-based Docker builds) and CI caching strategies
 * Track record of diagnosing and resolving slow builds and flaky tests at scale and implementing pragmatic fixes and guardrails
 * Strong systems thinking: experience with capacity planning for CI, agent provisioning/auto-scaling, and productionizing developer tooling
 * Experience integrating AI into developer workflows (AI-assisted development tooling and process, prompt engineering, model-backed services/APIs) and building developer UX around model behavior (explainability, sandboxing, versioned APIs)
 * Strong understanding of privacy, security, and governance for ML systems (data minimization, PII handling, differential privacy or anonymization practices, model access controls)
 * Experience designing observability for platform services and developer productivity metrics
 * Excellent communication, stakeholder management and mentorship skills; ability to influence without formal authority
 * Experience with Agile Software Development, Scrum, SAFe, * History of replacing or platformizing home-grown build tooling
 * Experience with JUnit5/TestNG and Spring Boot modernization
 * Prior ownership of developer platform(s) or developer experience initiatives with demonstrated impact (reduced cycle time, lower flake rate, or improved release cadence)

## Description

Autodesk's PLM engineering team is hiring a Senior Software Development Engineer, a backend developer who will own and accelerate developer productivity and the low-level modernization work that enables the next generation of our PLM platform. You will design and deliver platform-level solutions (build, CI/CD, testing, observability, developer tooling and workflows) that measurably reduce developer cycle time, increase release confidence, and scale across teams. This role requires deep systems thinking, a pragmatic engineering approach, and the ability to influence and partner across architects, product, and multiple engineering teams., * Own the technical modernization roadmap for backend developer productivity: define priorities, success metrics, and the execution plan

 * Design and implement scalable, secure, and maintainable cross-cutting systems (builds, CI pipelines, test platforms, artifact/agent provisioning)
 * Build, operate and iterate on developer platforms and tooling (multi-module build systems, CI caching, agent autoscaling, flaky test detection and mitigation)
 * Diagnose and fix large, hard problems: slow builds, flaky tests, brittle integration flows, and bottlenecks that harm developer velocity
 * Drive engineering excellence through strong design and code reviews, automated testing strategies, and operational best practices (SLOs, alerts, playbooks)
 * Lead cross-team modernization initiatives-coordinate with Architects, Product Managers, UX, and other engineering groups to deliver platform capabilities that serve many teams
 * Mentor and influence engineers and technical leads across teams: grow technical depth, shared ownership, and healthy engineering practices
 * Adopt modern, pragmatic AI-assisted development practices by using AI coding agents to deliver production features, refactors, and fixes with strong verification (tests, CI, code review)
 * Proactively surface and mitigate technical risks, performance issues, and operational limitations


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