Principal Systems Development Engineer
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What you'll do
- Serve as the Product Owner and Enterprise Architect for Agentic AI enablement products and engineering platforms.
- Maintain deep technical expertise and hands-on knowledge of enterprise application architecture, cloud platforms, AI technologies, integration frameworks, and modern software engineering practices.
- Define product vision, strategy, roadmap, requirements, and success metrics for AI-powered engineering productivity solutions.
- Drive the transformation from traditional engineering processes to AI-native workflows leveraging intelligent assistants, AI agents, and automation.
- Lead the design and governance of Agentic AI ecosystems, including Model Context Protocol (MCP), agent orchestration, lifecycle management, security, and compliance.
- Partner with hardware, firmware, software, systems engineering, and business stakeholders to identify and prioritize high-value AI transformation opportunities.
- Develop enterprise data and integration strategies supporting Generative AI, RAG, semantic search, knowledge management, and autonomous workflows.
- Modernize legacy applications and drive adoption of scalable cloud-native engineering platforms.
- Establish technology standards, architecture principles, governance frameworks, and engineering best practices.
- Influence executive leadership and provide technical direction across multiple organizations.
What they're looking for
- Master's or Bachelor's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Software Engineering, Computer Engineering, Information Systems, or a related technical field.
- 10+ years of experience in software engineering, systems development, platform engineering, product management, enterprise architecture, or related technical leadership roles.
- Proven experience serving as a Product Owner, Technical Product Leader, Enterprise Architect, or Principal Engineer for enterprise-scale platforms.
- Experience leading digital transformation, platform modernization, and engineering productivity initiatives.
- Strong expertise in cloud-native architectures, distributed systems, APIs, microservices, and enterprise integration patterns.
- Experience collaborating across hardware, firmware, software, and systems engineering organizations.
Nice to have
- Experience delivering Agentic AI, Generative AI, MCP, RAG, knowledge graph, or AI orchestration solutions.
- Experience building internal engineering productivity platforms and workflow automation solutions.
- Knowledge of PLM, ALM, DevOps, Engineering Lifecycle Management, and related engineering toolchains.
- Experience with Azure, Kubernetes, DevSecOps, Infrastructure as Code, and platform engineering practices.
- Master's degree in Engineering, Computer Science, Artificial Intelligent.
Summarised by NextRaise from the employer’s description, which follows in full below.
Full description from employer
Principal Systems Development Engineer - Enterprise Architecture for AI-enabled engineering applications and platforms
Job Summary:
Dell Technologies is seeking a highly experienced Principal Systems Development Engineer to serve as the Product Owner and Enterprise Architect for next-generation AI-enabled engineering applications and platforms. This role will drive the transformation of engineering systems, processes, and workflows through Agentic AI, intelligent automation, cloud-native architectures, and modern data platforms. The ideal candidate will combine product leadership, enterprise architecture expertise, and AI transformation experience to define platform vision, roadmap, business capabilities, and technical architecture while driving adoption of intelligent agents, automation frameworks, and AI-native operating models across the enterprise.
Key Responsibilities:
- Serve as the Product Owner and Enterprise Architect for Agentic AI enablement products and engineering platforms.
- Maintain deep technical expertise and hands-on knowledge of enterprise application architecture, cloud platforms, AI technologies, integration frameworks, and modern software engineering practices.
- Define product vision, strategy, roadmap, requirements, and success metrics for AI-powered engineering productivity solutions.
- Drive the transformation from traditional engineering processes to AI-native workflows leveraging intelligent assistants, AI agents, and automation.
- Lead the design and governance of Agentic AI ecosystems, including Model Context Protocol (MCP), agent orchestration, lifecycle management, security, and compliance.
- Partner with hardware, firmware, software, systems engineering, and business stakeholders to identify and prioritize high-value AI transformation opportunities.
- Develop enterprise data and integration strategies supporting Generative AI, RAG, semantic search, knowledge management, and autonomous workflows.
- Modernize legacy applications and drive adoption of scalable cloud-native engineering platforms.
- Establish technology standards, architecture principles, governance frameworks, and engineering best practices.
- Influence executive leadership and provide technical direction across multiple organizations.
Required Qualifications:
- Master's or Bachelor's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Software Engineering, Computer Engineering, Information Systems, or a related technical field.
- 10+ years of experience in software engineering, systems development, platform engineering, product management, enterprise architecture, or related technical leadership roles.
- Proven experience serving as a Product Owner, Technical Product Leader, Enterprise Architect, or Principal Engineer for enterprise-scale platforms.
- Experience leading digital transformation, platform modernization, and engineering productivity initiatives.
- Strong expertise in cloud-native architectures, distributed systems, APIs, microservices, and enterprise integration patterns.
- Experience collaborating across hardware, firmware, software, and systems engineering organizations.
Preferred Qualifications:
- Experience delivering Agentic AI, Generative AI, MCP, RAG, knowledge graph, or AI orchestration solutions.
- Experience building internal engineering productivity platforms and workflow automation solutions.
- Knowledge of PLM, ALM, DevOps, Engineering Lifecycle Management, and related engineering toolchains.
- Experience with Azure, Kubernetes, DevSecOps, Infrastructure as Code, and platform engineering practices.
- Master's degree in Engineering, Computer Science, Artificial Intelligent.
Compensation
Dell is committed to fair and equitable compensation practices. The salary range for this position is $170,000 - 200,000.
Benefits and Perks of working at Dell Technologies
Your life. Your health. Supported by your benefits. You can explore the overall benefits experience that awaits you as a Dell Technologies team member — right now at MyWellatDell.com
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