Principal Engineer - Agentic AI

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  Define Autodesk's technical vision and reference architecture for enterprise Agentic AI platforms

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  Lead the design and development of scalable multi-agent systems capable of planning, reasoning, memory management, and tool orchestration

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  Establish engineering standards, architectural patterns, governance models, and best practices for AI agent development

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  Serve as the technical authority for complex AI platform initiatives spanning multiple business units

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  Design reusable Agentic AI platform capabilities, including agent orchestration, memory services, context management, tool execution frameworks, Retrieval-Augmented Generation (RAG), Model Context Protocol (MCP) integration, agent-to-agent communication, and human-in-the-loop workflows

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  Build highly available, secure, cloud-native AI services using Kubernetes and modern cloud platforms

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  Drive platform observability, resilience, reliability, and operational excellence

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  Architect integrations with leading foundation models and AI service providers

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  Optimize AI agent workflows for latency, reliability, quality, scalability, and cost efficiency

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  Implement evaluation frameworks for reasoning quality, hallucination detection, safety, and overall AI system performance

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  Develop reusable Software Development Kits (SDKs), Application Programming Interfaces (APIs), engineering frameworks, and accelerators for AI product teams

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  Define enterprise standards for AI governance, security, compliance, privacy, and Responsible AI practices

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  Partner with Legal, Security, Privacy, and Trust teams to implement secure AI deployment patterns and enterprise guardrails

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  Lead Product Management partnerships to define AI platform roadmaps and long-term technical strategy

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  Mentor senior technical leaders, Principal Engineers, and engineering teams across Autodesk

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  Influence engineering strategy through architectural reviews, technical leadership, and cross-functional collaboration

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  Drive adoption of AI engineering best practices through documentation, technical workshops, and engineering communities

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  Evaluate emerging AI technologies, frameworks, and research to inform Autodesk's long-term AI strategy

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  Prototype advanced autonomous capabilities using state-of-the-art reasoning, planning, and orchestration techniques

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  Represent Autodesk at technical conferences, standards organizations, and industry collaborations

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  Contribute to strategic technology investments and long-term AI platform vision

• Bachelor's degree in Computer Science, Engineering, or a related field, with a Master's degree or Doctor of Philosophy (PhD) preferred

• 15+ years of software engineering experience, including significant experience building distributed systems and cloud-native platforms

• 5+ years of experience designing enterprise-scale Artificial Intelligence (AI), Machine Learning (ML), or intelligent automation platforms

• Demonstrated experience leading architecture and technical strategy across multiple engineering organizations

• Strong programming skills in one or more languages such as Python, Java, Go, or C++

• Deep expertise with cloud platforms, including Amazon Web Services (AWS), Microsoft Azure, or Google Cloud Platform (GCP)

• Experience with Kubernetes, containers, microservices, and event-driven architectures

• Expertise with Representational State Transfer (REST) Application Programming Interfaces (APIs), GraphQL, gRPC, messaging systems, and service mesh technologies

• Exceptional technical leadership, communication, and stakeholder management skills

• Experience building and deploying production-grade autonomous AI agents

• Deep understanding of multi-agent architectures, planning and reasoning systems, tool calling, function execution, long-term memory architectures, workflow orchestration, and AI evaluation methodologies

• Experience with foundation models such as OpenAI, Anthropic, Google Gemini, or equivalent technologies

• Experience using AI frameworks such as LangGraph, LangChain, Semantic Kernel, CrewAI, AutoGen, LlamaIndex, or similar platforms

• Experience with vector databases, Retrieval-Augmented Generation (RAG) architectures, knowledge graphs, and Model Context Protocol (MCP)

• Familiarity with AI observability, monitoring, and evaluation platforms

• Experience with enterprise-scale platform engineering, identity and access management, Zero Trust security architectures, API management, enterprise integration patterns, DevSecOps, and Machine Learning Operations (MLOps)

• Experience defining enterprise technology strategy and driving organization-wide engineering transformation

The ideal candidate is a visionary engineering leader who combines deep expertise in Artificial Intelligence (AI), distributed systems, and enterprise architecture with the ability to influence technology strategy and deliver innovative, scalable platforms that drive business impact

• Demonstrates exceptional expertise in designing and building enterprise-scale AI platforms and cloud-native distributed systems

• Defines long-term technical vision while balancing innovation, scalability, security, reliability, and operational excellence

• Solves highly complex technical challenges by applying sound architectural judgment, analytical thinking, and industry best practices

• Influences engineering strategy across multiple organizations through technical leadership and architectural guidance

• Drives innovation by evaluating emerging AI technologies and translating research into production-ready capabilities

• Establishes engineering standards, governance models, and reusable frameworks that improve platform quality and developer productivity

• Builds trusted partnerships with executive leadership, engineering teams, product organizations, and cross-functional stakeholders

• Mentors senior engineers, Principal Engineers, and technical leaders while fostering a culture of engineering excellence and continuous learning

• Communicates complex technical concepts effectively to both technical and executive audiences

• Demonstrates a customer-first mindset and aligns technical decisions with long-term business objectives

• Operates with a high degree of ownership, accountability, and strategic influence while delivering measurable outcomes

• Champions Responsible AI, security, privacy, and governance as foundational principles for enterprise AI solutions

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