Staff Software Engineer

Drive the design and development of the next generation of agentic, reliable, and scalable GenAI platforms supporting state-of-the-art large language models, evaluation systems, and secure developer tooling. Shape technical direction, ensuring architectural excellence to infuse AI into real-world production solution. Lead the design and development of secure, scalable platform services and tooling for LLM-powered applications, agentic workflows, and experimentation. Design and implement retrieval and knowledge systems (e.g., RAG pipelines, embeddings, vector stores) to support enterprise use cases. Establish evaluation frameworks, benchmarks, and feedback loops to measure and continuously improve quality, correctness, and safety of GenAI systems. Build observability and debugging capabilities for LLM applications, including tracing, cost monitoring, latency analysis, and failure detection. Optimize cost and performance of GenAI workloads through model routing, caching, prompt optimization, and efficient infrastructure design. Architect multi-tenant capabilities including isolation, configuration, quota management, and cost attribution. Implement GenAI-specific security controls, including prompt injection mitigation, data protection, and access governance. Design and implement agent orchestration frameworks, including tool integration, state management, and workflow control. Build developer-facing APIs, SDKs, and tooling to enable rapid experimentation and productionization of GenAI use cases. Drive end-to-end lifecycle management from experimentation to production, including versioning, deployment strategies, and rollback mechanisms. Integrate and evaluate multiple model providers and frameworks, defining abstraction and selection strategies. Develop Software using C#, Java, JavaScript, Go, or Python. Apply experience with generative AI, large language models (LLMs), and cloud infrastructure. Work with GenAI platform technologies (MCP, LangGraph, OpenAI, Bedrock). Option to telecommute 3 days per week. Bachelors degree in Computer Science, Computer or Software Engineering or Information Systems plus 5 years of experience in the job offered or in a related occupation.