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Tiger Analytics is looking for experienced Forward Deployed Engineer with Gen AI experience to join our fast-growing advanced analytics consulting firm. Our employees bring deep expertise in Machine Learning, Data Science, and AI. We are the trusted analytics partner for multiple Fortune 500 companies, enabling them to generate business value from data. Our business value and leadership has been recognized by various market research firms, including Forrester and Gartner.

We are looking for top-notch talent as we continue to build the best global analytics consulting team in the world.

Role Overview

We're looking for a Forward Deployed Engineer who thrives at the intersection of client problem-solving and hands-on AI engineering. You'll partner directly with clients and engineering teams to turn complex business challenges into production-grade GenAI and Agentic AI solutions — owning the journey from first conversation to live deployment.

Requirements

• 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 closely with architects, ML engineers, developers, and client stakeholders in fast-moving, ambiguous environments.

Qualifications

Engineering Foundation

• 7+ years in software engineering, application development, ML engineering, or AI engineering.
• Strong Python programming skills.
• Solid grasp of APIs, system design, databases, cloud-native applications, and production deployments.
• JavaScript/TypeScript experience is a plus.

GenAI / Agentic AI Expertise

• Proven experience building and deploying end-to-end GenAI and/or Agentic AI solutions.
• Hands-on experience with LLMs — OpenAI, Anthropic Claude, Google Gemini, and open-source models.
• Hands-on experience with RAG, vector databases, embeddings, tool/function calling, and AI agents.
• Experience with agent orchestration, multi-agent systems, or agentic workflows.
• Familiarity with frameworks such as LangGraph, LangChain, LlamaIndex, Google ADK, or similar.