GenAI Forward Deployed Engineer - Client-Facing AI

Tiger Analytics Inc.; Atlanta (GA); On-site; USD 130,000 - 190,000; Full time

Job summary

Tiger Analytics Inc. is seeking a Forward Deployed Engineer with GenAI expertise to partner directly with clients and engineering teams.

You will turn complex business challenges into production-grade GenAI and Agentic AI solutions, owning the journey from initial conversation to live deployment. Responsibilities include designing and scaling LLM applications, integrating AI with enterprise data and APIs, and deploying across cloud environments.

Qualifications

• 7+ years in software engineering, application development, ML or AI engineering.
• Strong Python programming skills.
• Solid grasp of APIs, system design, databases, cloud-native apps, and production deployments.
• Hands-on experience with LLMs (OpenAI, Claude, Gemini, etc.).
• Experience with RAG, vector databases, embeddings, tool/function calling, and AI agents.

Responsibilities

• Partner directly with clients to understand complex business problems and translate them into GenAI and Agentic AI solutions.
• Design, build, deploy, and scale LLM applications, RAG systems, AI agents, and multi-agent workflows.
• Integrate AI solutions with enterprise data, APIs, databases, and business applications.
• Deploy, operate, and scale solutions in production cloud environments.
• Troubleshoot and optimize production systems for performance, scalability, reliability, security, and cost.
• Collaborate with architects, ML engineers, developers, and client stakeholders in fast-moving environments.

Skills

Python

APIs & System Design

Cloud-Native Deployments

OpenAI/LLMs

JavaScript/TypeScript

Tools

LangGraph

LangChain

LlamaIndex

Google ADK

Bedrock

Job description

Tiger Analytics Inc. is seeking a Forward Deployed Engineer with GenAI expertise to partner directly with clients and engineering teams.

You will turn complex business challenges into production-grade GenAI and Agentic AI solutions, owning the journey from initial conversation to live deployment. Responsibilities include designing and scaling LLM applications, integrating AI with enterprise data and APIs, and deploying across cloud environments.