Software Architect

Job description

Job Requisition ID # 26WD94741 Position Overview Autodesk is undertaking a bold transformation to become an AI-first application platform, delivering a seamless, unified experience that fundamentally reshapes how customers and internal teams design, build, and operate within an agent-driven workspace. This platform will serve as the foundation for the next generation of Autodesk’s Design and Make software. We are seeking a Software Architect for Agentic AI Initiatives to define, architect, and deliver advanced AI systems capable of autonomous reasoning, decision-making, and self-directed execution. This is a senior, highly influential role that blends deep technical expertise with architectural leadership and strategic vision. You will collaborate closely with engineering, product, research, and business leaders to build domain-aware intelligent systems that accelerate innovation and deliver measurable impact across the Autodesk platform. Responsibilities Architecture & Development • Architect, design, and guide the development of AI systems, including autonomous agents, multi-agent frameworks, and LLM-powered agents. • Define reference architectures, patterns, and best practices for integrating agentic AI into existing Autodesk platforms, services, and workflows. • Drive architectural decisions across inference, orchestration, tool integration, memory, and feedback loops. Research, Prototyping & Evaluation • Evaluate emerging AI models, frameworks, and tooling. • Prototype, benchmark, and assess solutions for scalability, robustness, safety, cost efficiency, and performance. • Translate research and experimentation into production-ready architectural guidance. Production Deployment & Operational Excellence • Guide the deployment of agentic AI solutions into production environments with a focus on reliability, resilience, and operability. • Define strategies for monitoring agent behavior, detecting anomalies, and refining agent policies. • Establish feedback mechanisms for continuous learning, evaluation, and system improvement. Ethics, Safety & Governance • Ensure agentic AI systems adhere to ethical principles, regulatory requirements, and Autodesk governance standards throughout their lifecycle. • Champion best practices for data privacy, security, auditability, and responsible AI usage. Cross-Functional Leadership & Communication • Partner closely with platform architects, software engineers, applied AI teams, product managers, and business stakeholders. • Clearly communicate complex architectural concepts, trade-offs, and risks to both technical and non-technical audiences. • Act as a technical thought leader and mentor within the organization Minimum Qualifications • Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field (or equivalent practical experience) • 15+ years of professional software engineering experience, including at least 5 years in AI/ML engineering or architecture roles. • Demonstrated experience designing and delivering complex, production-grade software systems. • Deep understanding of AI/ML algorithms, architectures, and frameworks. • Proven experience delivering AI-powered features or platforms in large-scale software products. • Strong ability to work effectively across multidisciplinary, cross-functional teams. • API and service design at scale (REST, gRPC, GraphQL), including versioning and backward compatibility. • Distributed systems and data platforms, including microservices, service mesh, and streaming processing architectures. • Excellent written and verbal communication skills, with the ability to explain complex technical concepts to non-technical stakeholders. • Strong analytical and systems-thinking skills, with a track record of solving complex technical challenges. • Ability to think strategically about the future of AI and its application to design, construction, manufacturing, and infrastructure industries. Preferred Qualifications • Experience deploying and operating AI solutions at scale on major cloud platforms (AWS, Azure, or Google Cloud Platform). • Strong experience with AWS services, such as EC2, ECS, Lambda, API Gateway, S3, DynamoDB, and RDS. • Database architecture and technologies, including relational and NoSQL systems. • Event-driven and streaming architectures (Kafka or Kinesis), including exactly-once processing and schema evolution (Avro / Protobuf). • Observability and SRE practices: OpenTelemetry, distributed tracing, metrics, SLIs/SLOs. • Knowledge graphs and semantic modeling (nice-to-have): RDF/OWL, property graphs, or ML feature stores. • Hands-on experience with RAG architectures, including embeddings, vector stores, chunking strategies, re-ranking, and retrieval evaluation. • Experience with agent orchestration frameworks (e.g., LangGraph, Semantic Kernel), function/tool calling, and assistants-style APIs. • AI data governance, privacy, and safety practices, including PII handling, prompt-injecti