Senior Software Engineer, Agentic AI Systems

## Responsibilities - Design and implement intelligent systems that can reason, plan, and execute complex multi-step workflows. - Develop architectures that combine LLMs, retrieval systems, memory, tools, and feedback loops. - Build autonomous and semi-autonomous workflows that improve engineering productivity and operational efficiency. - Design scalable backend services, APIs, and distributed systems supporting AI-native applications. - Build orchestration frameworks for multi-agent and tool-based systems. - Develop evaluation frameworks that measure accuracy, reliability, latency, and task completion. - Partner with AI researchers, infrastructure teams, product teams, and software engineering organizations. ## Requirements - BS, MS, or PhD in Computer Science, Computer Engineering, or a related field. - 5+ years of software engineering experience. Strong proficiency in Python and modern software development practices. - Experience building scalable distributed systems and cloud-native services. Experience developing AI-enabled applications using LLMs, RAG, agent frameworks, or workflow orchestration systems. - Proven experience designing, building, and operating large-scale production software systems. - Strong understanding of distributed systems, scalability, reliability, observability, and performance engineering. - Demonstrated ability to own services from architecture and implementation through production operations and long-term maintenance. - Ability to balance rapid innovation with engineering rigor, maintainability, and operational excellence. ## Nice to Have - Experience building production AI agents or autonomous systems. Experience with reasoning frameworks, planning systems, memory architectures, and tool-use ecosystems. - Experience with vector databases, retrieval systems, knowledge graphs, or semantic search. Experience with AI evaluation, benchmarking, and observability platforms. - Built and operated business-critical platforms serving large user bases or high-volume workloads. - Experience modernizing early-stage prototypes into robust production systems. - Deep expertise in system architecture, reliability engineering, and technical leadership. Track record of reducing operational complexity while increasing scalability and maintainability. ## Benefits - The ideal candidate has experience architecting and operating large-scale, production-grade software that remains reliable, maintainable, and extensible as it grows. While AI expertise is valuable, we place equal importance on strong software engineering fundamentals, system design, operational excellence, and long-term ownership. We are looking for engineers who see AI agents not as prompts, but as software systems.