Position Overview  

Autodesk's Architecture, Engineering, and Construction (AEC) Platform Data organization is seeking an experienced Software Architect. 

In this role, you will be responsible for designing and building the systems and services that power cross-cutting data capabilities across our organization and their integration with Autodesk's existing and future AEC products.  

This opportunity is for you if you have a passion for the design of complex system architectures and are excited by the idea of transforming how AEC professionals use data to capture knowledge, inform decisions, and deliver projects.   

As a Software Architect in the AEC Platform Data, you will be at the forefront of designing the next generation of capabilities for the Autodesk Forma Industry Cloud. You'll collaborate with software architects in the AEC Platform Data team as well as with software architects from the world's foremost applications and services for designing and constructing buildings and infrastructure, including Revit, Civil 3D, AutoCAD, the Autodesk Construction Cloud, and Autodesk Forma. You'll define the software architecture that reimagines the continuous flow of AEC Data (e.g. 3D models, 2D drawings, issue tracking, cost, sensor streams, etc.) and information throughout the entire lifecycle of a built asset, from design and construction through operation and maintenance.    

This is an individual contributor role reporting to the Distinguished Architect, AEC Platform Data team.  

Responsibilities  

• Define and evolve cross-team architecture for data platforms and services in AEC Platform Data organization 

• Establish standards, reference architectures, and reusable components; drive adoption across teams in the AEC Platform Data organization 

• Lead architectural governance and architectural decision records (ADRs); run design reviews across teams  

• Design and guide implementation of distributed systems and data platforms (APIs, schemas, event streams; batch and streaming)  

• Ensure reliability, security, and performance; define SLOs and drive observability (metrics, tracing, logging)  

• Partner across the AEC organization’s product and platform teams to align roadmaps and integrations 

• Communicate architectures with clear views and diagrams (e.g., C4) and executive-ready narratives  

Minimum Qualifications  

• Bachelor's degree in computer science, or equivalent experience  

• 10+ years as a Software Architect in data-intensive cloud environments  

• Experience with cloud services, API design, database architecture, big data tools and frameworks  

• Strong understanding of data modeling, management and processing principles  

• Excellent knowledge of software design and architecture  

• Demonstrated ability to influence without authority and drive cross-team alignment 

• Mastery of taking complex ideas and conveying them in a concise and impactful manner  

• Excellent verbal, written communication, and presentation abilities to effectively communicate software architecture strategy to a variety of stakeholders  

• Ability to collaborate with a global team  

Preferred Qualifications  

• Experience in the Architecture, Engineering, and Construction industry  

• Cloud services experience with AWS strongly preferred (EC2, ECS, Lambda, API Gateway, S3, DynamoDB, RDS) 

• Database architecture and technologies: Snowflake, relational, NoSQL 

• Event-driven and streaming architectures: Kafka or Kinesis; exactly-once processing; schema evolution (Avro/Protobuf) 

• API and service design: REST, gRPC, GraphQL; versioning and backward compatibility at scale 

• Distributed systems and data platforms: microservices, service mesh, event-driven architecture, streaming processing 

• Observability/SRE: OpenTelemetry, distributed tracing, metrics/SLOs for data services 

• Knowledge graphs/semantic modeling (nice-to-have): RDF/OWL, property graphs, or feature stores for ML 

• Experience designing and integrating AI systems and agents in enterprise environments; familiarity with Model Context Protocol (MCP) and tool/plugin ecosystems  

• Hands-on with RAG architectures: embeddings, vector stores, chunking, re-ranking, and retrieval evaluation 

• Experience with agentic orchestration frameworks (e.g., LangGraph, Semantic Kernel) and function/tool calling; Assistants-style APIs 

• Data governance, privacy, and safety for AI systems (PII handling, prompt-injection defenses, content filtering, auditability)  

• LLM observability and evaluation: offline/online evals, guardrails, prompt/version management and telemetry (e.g., LangSmith, PromptFlow, OpenTelemetry)  

• Domain-specific AI for AEC (nice-to-have): extracting structure from BIM/IFC and construction docs; CAD/point-cloud processing