Builds agentic AI systems, MCP servers, retrieval systems, and evaluation pipelines for reliable AI-generated code. Responsibilities include supporting large-codebase changes, implementing compile and test gates, applying concurrency and telemetry best practices, improving performance and safety, and collaborating on AI workflow experiments. The role requires Java or Python proficiency, production or developer-facing systems experience, strong communication, and a computer science foundation.

Lead and mentor AI engineers while directing the architecture of an agentic AI platform spanning agents, MCP servers, retrieval systems, and financial workflows. Build evaluation, testing, static analysis, and quality pipelines for AI-generated code. Establish engineering standards for reliability, observability, concurrency, prompt versioning, and performance. Lead experimentation, technical escalations, stakeholder communication, and secure handling of sensitive financial data.

Conduct firm mapping, market research, prospect building, lead generation, and client movement analysis. Prepare reports, educational decks, proposals, RFP/RFQ responses, and customized tracking tools. Support client relationship management, marketing strategy, outreach optimization, cross-selling initiatives, and business expansion while maintaining information security and complying with IT policies.