Senior Software Engineer, Agentic AI

Role overview Build and operate cloud services that support product access for a large global user base. This senior engineering role covers the full service lifecycle, from requirements and design through delivery and production support, and also develops agent-based automation for engineering and operational work. The position includes shared production on-call duties.

Responsibilities - Design, develop, and run resilient Java microservices and distributed systems on AWS. - Own features and platform initiatives through requirements, implementation, testing, operational readiness, and ongoing support. - Improve service reliability, scalability, performance, and security; troubleshoot incidents and lead root-cause analysis. - Plan and drive medium-to-large engineering initiatives, including scope, estimates, and schedules. - Build agent capabilities such as reusable skills, tool integrations, and retrieval grounded in runbooks, tickets, and service documentation. - Add evaluation, CI quality gates, observability, and human review controls to production agent workflows; participate in the shared on-call rotation.

Requirements - Bachelor’s degree or higher in computer science, engineering, or a related field, or equivalent practical experience. - At least six years building and operating Java microservices and serverless systems in production. - Strong Java and Spring Boot skills, with experience in unit, integration, and system testing and practical debugging. - Hands-on experience building or integrating AI systems such as agents, LLM applications, retrieval-augmented generation, or tool-calling workflows. - Experience with spec-driven development and event streaming, containers, CI/CD, and core AWS services. - Clear communication and collaboration skills, with readiness to share responsibility for design, delivery, and production support.

Nice to have - Python and FastAPI, MCP servers or similar agent tool frameworks, RAG, agent evaluation, multi-agent patterns, or human-in-the-loop review. - Familiarity with Kinesis or Kafka, AWS messaging and serverless services, OpenTelemetry, AI tracing, Gradle or Maven, access policies, OAuth, and responsible AI practices.

Benefits and work setup - Shared on-call work may include support outside standard business hours, according to the team schedule. The listing describes health, financial, time-away, and wellness benefits. U.S. base pay is listed as $117,000–$209,330, depending on experience and location.