Lead AI Engineer - Agentic Engineering
Lead the design and delivery of production-grade agentic AI systems while embedding AI agents into software development workflows to improve engineering productivity, reliability, and quality.
The Lead AI Architect & Delivery Manager will serve as the technical authority and engagement lead for the client's TPRM AI Assistant project, backfilling the departing AI Lead. This role is responsible for driving the technical strategy of the Snowflake-native RAG solution, orchestrating the offshore engineering team, interfacing directly with FCB leadership (ED&A, TPRO, InfoSec SMEs), and ensuring the solution meets its tight production launch milestone.
Requirements
Benefits
Significant career development opportunities exist as the company grows. The position offers a unique opportunity to be part of a small, fast-growing, challenging and entrepreneurial environment, with a high degree of individual responsibility.
Tiger Analytics provides equal employment opportunities to applicants and employees without regard to race, color, religion, age, sex, sexual orientation, gender identity/expression, pregnancy, national origin, ancestry, marital status, protected veteran status, disability status, or any other basis as protected by federal, state, or local law.
Lead the design and delivery of production-grade agentic AI systems while embedding AI agents into software development workflows to improve engineering productivity, reliability, and quality.
Lead client-facing engineering engagements to design, build, and govern production-grade Claude agents, combining hands-on development, solution architecture, team leadership, and reusable delivery practices.
Lidera tecnicamente o desenvolvimento de ferramentas, protรณtipos e soluรงรตes com IA, transformando hipรณteses de negรณcio em MVPs e orientando decisรตes de arquitetura, produto e evoluรงรฃo com base em aprendizado e impacto.
Lead the technical direction of an AI engineering team, designing and delivering production-grade AI agents, LLM integrations, and enterprise workflow capabilities while remaining hands-on in development.
Design, build, and deploy production AI solutions for enterprise clients, owning work across architecture, application development, agentic workflows, cloud deployment, evaluation, and operationalization.