Sr. Staff Applied AI Engineer, GTM
Build secure, production-grade AI solutions for go-to-market teams while shaping AI strategy, advising leaders, and measuring impact on revenue outcomes and seller productivity.
Tiger Analytics is seeking a highly experienced Lead AI Engineer to lead the end-to-end AI Engineering workstream for the Luma platform. This is a hands-on technical leadership role responsible for driving the architecture, design, and delivery of enterprise-scale Agentic AI solutions while serving as the primary technical interface for the client.
We are looking for a Forward Deployed AI Engineer to build and deploy enterprise GenAI, RAG, Agentic AI, and Knowledge Graph solutions. The role involves working directly with customers, rapidly developing POCs/MVPs, and taking solutions into production.
Requirements
LangChain, LlamaIndex, LangGraph, AutoGen, GraphRAG, Vector DBs, AWS Bedrock, Azure OpenAI, Kubernetes, Docker, Terraform, vLLM/Triton, PyTorch/Hugging Face.
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.
Build secure, production-grade AI solutions for go-to-market teams while shaping AI strategy, advising leaders, and measuring impact on revenue outcomes and seller productivity.
Build the agent runtime, prompts, and evaluation systems that help an AI coworker use tools reliably, handle long-running work, and act safely through approvals and safeguards.
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.
Shape AI architecture and technical strategy for enterprise-scale systems, delivering production-ready agentic AI, safety controls, real-time data pipelines, and scalable SaaS capabilities.
Lead technical delivery of customer-facing AI workflows, connecting AI assistance to application state and authorized actions while improving reliability, evaluation, and measurable customer outcomes.