Applied AI Senior Principal Developer

About the Role

In this senior technical leadership position you will lead the design and delivery of foundational applied AI capabilities that directly impact product experience and customer outcomes. Responsibilities include owning system architecture, component design, and critical technical decisions for agent integration, agent stores, and production observability, as well as evaluating, prototyping, and operationalizing advanced model approaches such as LLM integrations, retrieval-augmented generation, hybrid architectures, and agentic components. You will define and enforce standards for agent and model governance, responsible AI, bias detection, explainability, and data privacy, while mentoring and technically coaching Applied AI engineers through architecture reviews, code reviews, and cross-team design sessions. Collaboration with product and UX partners will translate product goals into technical requirements, success metrics, and experiment strategies, and you will represent technical designs and trade-offs to leadership, support hiring, and help shape the Applied AI roadmap. • Lead design and delivery of large-scale applied AI systems that are production‑ready, reliable and maintainable • Evaluate, prototype, and operationalize advanced model approaches including LLM integrations, retrieval‑augmented generation, hybrid architectures, and agentic components • Define and enforce standards for responsible AI, bias detection, explainability, and data privacy • Mentor and coach Applied AI engineers; lead architecture reviews, code reviews, and cross‑team design sessions • Collaborate with product and UX partners to translate goals into technical requirements, success metrics, and experiment strategies • Represent technical designs and trade‑offs to leadership, support hiring, and help define the Applied AI roadmap • Design low‑latency, real‑time inference systems and reason about performance, reliability, security, and cost trade‑offs

Key Responsibilities

• ▸ai design
• ▸model prototyping
• ▸inference systems
• ▸responsible ai
• ▸architecture review
• ▸product collaboration

What You Bring

Minimum qualifications include 10+ years of software or ML engineering experience with a proven track record delivering production ML systems at scale, strong C++ and TypeScript expertise for desktop and web integration, and experience mentoring senior engineers and contributing to hiring. Candidates must have experience integrating third-party models and LLMs (including prompt engineering, RAG patterns, and safety controls), be able to design low-latency, real-time inference systems, and possess strong systems thinking, architecture, and performance, reliability, security, and cost trade-off skills. A bachelor’s degree in Computer Science, Engineering, or a related field is required, with an advanced degree preferred. Preferred qualifications are domain knowledge in architecture, engineering, construction (AEC), design, or manufacturing, solid cloud platform experience—preferably AWS—and familiarity with containerization and orchestration tools such as Docker and Kubernetes. Hands-on experience with responsible AI tooling, bias testing frameworks, and explainability platforms is also desired. • Own system architecture, component design, and technical decisions for agent integration, agent stores, and observability • 10+ years of software or ML engineering experience delivering production ML systems at scale • Strong C++ and TypeScript expertise for desktop and web integration • Experience mentoring senior engineers and contributing to hiring and technical culture • Experience integrating third‑party models and LLMs, including prompt engineering, RAG patterns, and safety controls • Excellent communication skills and ability to influence product, engineering, and business stakeholders • Bachelor’s degree in Computer Science, Engineering or related field (advanced degree preferred) • Domain knowledge in AEC, design, or manufacturing • Solid cloud platform experience (preferably AWS) and familiarity with Docker and Kubernetes • Hands‑on experience with responsible AI tooling, bias testing frameworks, and explainability platforms • Technical builder who sets high engineering standards and raises the bar • Thrives in fast‑paced, collaborative, matrixed environment and can influence without direct authority • Embodies One ORBIT values: optimism, outcome focus, smart risk‑taking, ingenuity, and trusted delivery

Requirements

• ▸c++
• ▸typescript
• ▸aws
• ▸docker
• ▸kubernetes
• ▸10+ years

Benefits

The ideal candidate is a technical builder who sets high engineering standards, thrives in a fast-paced, collaborative, matrixed environment, and can influence without direct authority. They demonstrate Autodesk’s One ORBIT values—optimism, relentless outcome focus, smart risk-taking, ingenuity, and trusted delivery and communication. Autodesk offers a competitive compensation package, flexible work environment, continuous learning opportunities, and a culture of diversity and belonging.

Work Environment

Hybrid