GenAI Forward Deployed Engineer — Production AI Solutions

Tiger Analytics Inc.; Dallas (TX); On-site; USD 140,000 - 210,000; Full time

Job summary

Tiger Analytics is seeking an experienced Forward Deployed Engineer with Gen AI expertise to partner 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, deploying, and scaling LLM applications, RAG systems, and AI agents; integrating AI with enterprise data and APIs; and deploying in cloud environments with focus on

Qualifications

• 7+ years of software engineering, ML or AI engineering experience.
• Hands-on with Python, APIs, system design, and cloud-native deployments.
• Experience building end-to-end GenAI/Agentic AI solutions with LLMs.

Responsibilities

• Translate client problems into GenAI/Agentic AI solutions and lead deployment.
• Design, build, deploy, and scale LLM apps, RAG systems, and AI agents.
• Integrate AI with enterprise data, APIs, databases, and business apps.
• Deploy, operate, and monitor production AI solutions in cloud environments.
• Collaborate with architects, ML engineers, and client stakeholders in fast-moving settings.

Skills

Python

APIs

System design

Databases

Cloud-native apps

Production deployments

JavaScript/TypeScript

LLMs

GenAI/Agentic AI

MCP/A2A protocols

Tools

LangGraph

LangChain

LlamaIndex

Google ADK

Bedrock

OpenSearch Serverless

Vertex AI

Semantic Kernel

Gemini APIs

Job description

Tiger Analytics is seeking an experienced Forward Deployed Engineer with Gen AI expertise to partner 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, deploying, and scaling LLM applications, RAG systems, and AI agents; integrating AI with enterprise data and APIs; and deploying in cloud environments with focus on