Design and build AI-enabled applications centered on knowledge graphs, ontologies, graph and vector databases, RAG, and agentic pipelines. Develop scalable backend systems, APIs, data pipelines, integrations, and interactive full-stack web applications. Make architectural decisions, integrate intelligent search and retrieval features, evaluate emerging technologies, and ship production code. Collaborate with product, design, domain experts, and leadership while contributing to engineering standards, quality, security, testing, and maintainability.

Owns client-facing quantum computing engagements from problem scoping through validated delivery. Develops, tests, benchmarks, and resource-estimates quantum algorithms and workflows for applications including cryptography, chemistry, finance, materials science, and defense. Serves as the primary technical client contact, translates domain problems into quantum computational tasks, communicates technical trade-offs, and collaborates with software engineers, scientists, and domain experts on commercial and government deliverables.

Build AI-powered tools that automate quantum application design, circuit construction, compilation, validation, and resource estimation. Develop LLM- and ML-driven pipelines, agentic workflows, and integrations with quantum SDKs, simulators, and analysis tools. Benchmark reliability and performance against expert baselines while collaborating with quantum algorithm scientists and customers. The role requires autonomous software delivery and strong Python, AI engineering, testing, and scientific computing skills.