Principal Network DevOps Engineer
Autodesk
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Job summary
Autodesk is seeking a Principal Network DevOps Engineer to join the Global Network Engineering team. You will help shape the SAAS platform that powers our products and enable scalable networking across cloud and on‑prem environments.
You'll lead automation initiatives, implement GitOps, and build AI-enabled operational platforms. Strong Python, Terraform, CloudFormation, and CI/CD experience are essential for success in this role.
Qualifications
- Bachelor’s Degree in CS or related field, or equivalent work experience.
- 7+ years of experience in software engineering, platform engineering, automation engineering, cloud engineering, infrastructure or network engineering.
- Strong expertise in Python development, API development, automation engineering, and software design.
Responsibilities
- Design and implement AI-driven operational platforms and intelligent automation solutions for network and cloud infrastructure
- Define and drive the technical vision, roadmap, and architecture for Autodesk’s global network and cloud connectivity platforms
- Build reusable automation services, integration components, SDKs, and orchestration capabilities
- Implement GitOps and CI/CD workflows across network platforms and automation services
- Establish engineering standards, design patterns, and best practices for network automation, Infrastructure-as-Code, and cloud networking
Skills
Education
Tools
Job description
Autodesk is looking for a Principal Network DevOps Engineer to join the Global Network Engineering team. Come join us in our journey to provide our customers with a world class SAAS platform, enabling imaginative and industry changing Autodesk products.
26WD98484
Autodesk is looking for a Principal Network DevOps Engineer to join the Global Network Engineering team. Come join us in our journey to provide our customers with a world class SAAS platform, enabling imaginative and industry changing Autodesk products.
- Design and implement AI-driven operational platforms and intelligent automation solutions for network and cloud infrastructure
- Build AI-powered assistants, decision-support systems, and operational intelligence capabilities
- Design autonomous and semi-autonomous workflow orchestration with multi-step reasoning and intelligent workflow execution
- Build AI-powered troubleshooting, diagnostics, incident triage, root cause analysis, and operational insight solutions
- Implement enterprise knowledge retrieval and Retrieval-Augmented Generation (RAG) capabilities, including context-aware systems that retrieve, correlate, analyze, and act on data from multiple enterprise sources
- Develop conversational and self-service experiences using modern collaboration and communication platforms
- Design human-in-the-loop approval workflows for operational, governance, security, and risk-sensitive activities
- Implement AI observability, evaluation, monitoring, governance, auditability, and lifecycle management capabilities
- Establish responsible AI, security, compliance, and governance standards
- Evaluate emerging AI technologies and drive enterprise adoption of AI-enabled operational capabilities
- Improve and engage in the entire lifecycle of a network, including inception, network design, qualification, deployment, operation, and optimization
- Work on implementation of Autodesk’s Global Networking backbone strategic infrastructure initiatives
- Define and drive the technical vision, roadmap, and architecture for Autodesk’s global network and cloud connectivity platforms
- Create and update our network standards and ensure that the network is deployed to these standards
- Design and develop scalable automation frameworks using Python, APIs, Infrastructure-as-Code (Terraform, CloudFormation, or similar), and modern automation technologies
- Build reusable automation services, integration components, SDKs, and orchestration capabilities
- Implement GitOps and CI/CD workflows across network platforms and automation services
- Automate provisioning, validation, compliance assessment, governance controls, and remediation workflows
- Develop self-service automation platforms for engineering and operational teams
- Establish engineering standards, design patterns, and best practices for network automation, Infrastructure-as-Code, and cloud networking
- Manage an enterprise scale SASE solution
- Design and develop integrations across enterprise systems, cloud platforms, operational tools, security platforms, ITSM tools, and knowledge repositories
- Build scalable connector and API integration frameworks using event-driven and API-first architectures
- Design secure data exchange and workflow orchestration services across distributed systems
- Collaborate with platform and cloud engineering teams to build scalable, resilient, and secure solutions
- Build enterprise knowledge platforms that use structured and unstructured sources, including documentation, runbooks, policies, standards, and operational records
- Develop knowledge ingestion, enrichment, classification, retrieval, search, summarization, and recommendation capabilities
- Improve knowledge discoverability and operational decision-making through intelligent knowledge systems
- Build automation supporting governance, risk, compliance, and audit requirements, including intelligent approval workflows and policy enforcement
- Design AI solutions that comply with enterprise security, privacy, and regulatory requirements
- Implement audit trails, traceability, explainability, and operational accountability controls
- Collaborate with Security and Compliance teams to establish enterprise AI governance standards
- Build observability, telemetry, monitoring, reporting, and operational intelligence platforms
- Create dashboards, alerts, health monitoring, and performance measurement capabilities
- Implement anomaly detection, predictive analytics, and operational reporting using metrics, logs, traces, events, and AI-driven insights
- Enable proactive operational management through intelligent analytics
- Bachelor’s Degree in CS or related field, or equivalent work experience
- 7+ years of experience in software engineering, platform engineering, automation engineering, cloud engineering, infrastructure or network engineering, or related technical disciplines
- Strong expertise in Python development, API development, automation engineering, and software design
- Hands-on experience with Infrastructure-as-Code (Terraform, CloudFormation, or similar), CI/CD, GitOps, and enterprise automation platforms
- Experience designing and implementing large-scale enterprise automation solutions
- Experience developing integrations across enterprise applications, cloud services, APIs, and operational platforms
- Strong understanding of cloud platforms including AWS, Azure, and/or GCP, with working knowledge of cloud networking and hybrid connectivity
- Demonstrated history of AWS experience with Transit Gateway, Direct Connect, Lambda, Route 53, VPC, and Cloud WAN
- Knowledge of firewalls, security configurations, and troubleshooting
- Strong analytical, troubleshooting, problem-solving, and system design skills
- Proven experience leading large-scale infrastructure initiatives and influencing technical strategy across multiple teams
- Proven ability to work effectively within an Agile framework
- Skilled at presenting technical policies, proposals, and designs
- Excellent communication, collaboration, and stakeholder engagement skills
- Ability to manage long term, project/milestone-based work with multiple teams
- Preferred: Experience designing and implementing Agentic AI solutions and intelligent automation platforms
- Preferred: Experience with Generative AI technologies and Large Language Models (LLMs)
- Preferred: Experience developing AI-powered assistants, workflow automation solutions, or intelligent operational platforms
- Preferred: Understanding of Retrieval-Augmented Generation (RAG), enterprise search, and knowledge integration patterns
- Preferred: Experience integrating AI solutions with APIs, operational platforms, monitoring systems, ITSM tools, and enterprise applications
- Preferred: Familiarity with AI governance, security, compliance, auditability, explainability, and responsible AI practices
- Preferred: Experience building conversational experiences and self-service automation platforms
- Preferred: Experience developing operational analytics, decision-support, workflow orchestration, or operational intelligence solutions
- Preferred: Experience supporting enterprise-scale AI adoption initiatives
- Preferred: Cisco CCNA
- Preferred: Cisco CCNP
Welcome to Autodesk! Amazing things are created every day with our software – from the greenest buildings and cleanest cars to the smartest factories and biggest hit movies. We help innovators turn their ideas into reality, transforming not only how things are made, but what can be made.
We take great pride in our culture here at Autodesk – it’s at the core of everything we do. Our culture guides the way we work and treat each other, informs how we connect with customers and partners, and defines how we show up in the world.
When you’re an Autodesker, you can do meaningful work that helps build a better world designed and made for all. Ready to shape the world and your future? Join us!
Salary is one part of Autodesk’s competitive compensation package. Offers are based on the candidate’s experience and geographic location. In addition to base salaries, our compensation package may include annual cash bonuses, commissions for sales roles, stock grants, and a comprehensive benefits package.
We take pride in cultivating a culture of belonging where everyone can thrive. Learn more here: https://www.autodesk.com/company/global-belonging
This role may require in-person onboarding and/or in-person ID verification.
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