Senior Software Engineer, Agentic AI
Autodesk · Portland, OR · 1 wk ago
Hybrid$117k–$209k/yrFull-time
About the role
We are seeking an experienced Senior Software Engineer to design, build, and operate resilient, scalable, high-performing services for the Product Access platform, which supports the access experience for millions of Autodesk users worldwide. You will own end-to-end solution design and delivery across the full engineering lifecycle and use spec-driven development and agentic systems to build, operate, and support Product Access in production, including agent-based automation for engineering and operational workflows.
Responsibilities
- Design, develop, and operate resilient, scalable, high-performing cloud-native Java microservices and distributed systems on AWS for the Product Access platform
- Own business features and platform initiatives end to end, from requirement analysis through production support, working with product and engineering partners on design, testing, and operational readiness
- Enhance system resiliency, reliability, scalability, and security; optimize performance, troubleshoot production issues, and implement engineering best practices across development and delivery pipelines
- Lead project delivery by organizing scope, estimating effort, establishing timelines, and driving medium-to-large initiatives independently
- Apply spec-driven development in platform and feature delivery
- Build and extend agentic systems and automation: composable skills, MCP integrations, and knowledge retrieval grounded in runbooks, tickets, and service documentation
- Deliver proactive triage and write-action automation with human-in-the-loop gates where required, progressing toward autonomous design-to-delivery workflows
- Enforce production standards for agentic systems through evaluation, CI quality gates, and end-to-end observability across agents and services
- Provide production support; lead incident response and root cause analysis; participate in a shared on-call rotation for production systems, including support outside standard business hours per team schedule; mentor engineers and uphold sound engineering practices
Requirements
- Bachelor's degree or higher in Computer Science, Engineering, or a related field, or equivalent practical experience
- 6+ years of progressive software engineering experience building and operating Java microservices and serverless architectures in production
- Strong Java and Spring Boot skills; solid unit, integration, and system testing; strong debugging in local and integrated environments
- Hands-on experience building or integrating AI-powered systems: agents, LLM-based applications, RAG, or tool-calling workflows
- Experience with spec-driven development (SDD)
- Experience with event-driven streaming (Kinesis, Kafka, or equivalent), containers on AWS (Docker, ECS Fargate), CI/CD (Jenkins, GitHub Actions), and core AWS services (Lambda, DynamoDB, messaging, API gateways, logging, monitoring)
- Strong collaboration and communication skills; effective in small teams with shared end-to-end ownership of design, delivery, and production support
Preferred Qualifications
- Proficiency in Python and FastAPI; experience building MCP servers or equivalent tool-use frameworks for AI agents
- Experience with RAG, proactive or event-driven agents, and applying agentic AI to engineering workflows, operational automation, or DevOps
- Designing LLM evaluation frameworks, multi-agent patterns, and human-in-the-loop review gates
- Familiarity with high-volume event pipelines (Kinesis/Kafka streaming, REST publish, SNS/SQS/DLQ patterns), Gradle or Maven, OpenTelemetry, and AI tracing tools (Opik, LangSmith, or equivalent)
- Understanding of policy-based access control (OPA), authentication for AI systems (OAuth, Entra ID), and Responsible AI practices
Technologies we use
- Platform: Java, Spring Boot; Python, FastAPI (agentic); AWS (ECS Fargate, Lambda, DynamoDB, SQS, API Gateway, CloudWatch, OpenSearch); Docker; GitHub; Jenkins / GitHub Actions; Gradle / Maven
- Streaming & events: Kinesis, Kafka, REST publish, SNS/SQS fan-out, DLQ handling, checkpointed consumers, multi-language event SDKs
- Observability & ops: Splunk, Kibana, Dynatrace, OpenTelemetry; Jira, Slack
- Agentic AI: LLM agents, MCP, RAG and vector retrieval, spec-driven development, evaluation and CI quality gates for production AI
- Security & access: OAuth, Entra ID, OPA and policy-based access control