Teams at EchoSpan

Lead and grow an Agentic AI engineering team to transition multi-agent and generative AI POCs into scalable, secure, production-grade LLM services. Define technical roadmap, ensure architectures support hybrid control flows and state machines, adopt agent interoperability standards, establish CI/CD and observability, and partner with product and business leaders to deliver measurable business impact.

Lead development and delivery of production-grade multi-agent AI systems: define technical strategy, mentor engineers, design scalable microservices, implement hybrid control flows and agent communication (MCP/A2A), conduct architecture reviews, and collaborate with product and business teams to drive LLM-powered solutions into production.

Design, build, and deploy production-grade autonomous AI services and multi-agent workflows. Implement secure agent-to-tool and agent-to-agent protocols (MCP, A2A), hybrid control flows, sandboxed execution, and SRE-driven observability. Collaborate with cross-functional teams to translate requirements into scalable microservices and reliable LLM-powered products.