Azure AI & UiPath Engineer — Enterprise AI Deployment

Tiger Analytics Inc.; United States; On-site; USD 140,000 - 210,000; Full time

Benefits offered by this job

Career development

Entrepreneurial environment

Job summary

Tiger Analytics is seeking an AI Engineer to drive on-site deployment, integration, and scaling of enterprise Generative AI solutions. You will embed within customer engineering teams to operationalize LLMs and retrieval systems across Azure, bridging research and production.

You will collaborate with cross-functional teams to ensure business value and communicate outcomes. The role emphasizes hands-on automation engineering, SDLC adherence (Agile/Scrum), and working with modern ML/AI frameworks

Qualifications

• 7+ years of industry experience in software engineering, machine learning, or AI-focused roles.
• Strong hands-on experience with LangGraph and building agentic workflows.
• Proven experience in fine-tuning LLMs, including supervised fine-tuning and reinforcement learning-based methods.
• Strong background in experimental design, model evaluation, and statistical analysis.
• Demonstrated ability to reduce hallucinations using techniques beyond creative prompting.
• Proficiency in Python and experience with modern ML/AI frameworks.

Responsibilities

• Deploy, integrate, and scale enterprise Generative AI solutions on-site within customer engineering teams.
• Operationalize Large Language Models (LLMs) and retrieval systems across Azure cloud.
• Bridge AI research and production-grade cloud infrastructure to deliver business value.
• Collaborate with cross-functional teams and business partners to shape strategy and communicate results.

Skills

LangGraph

Agentic workflows

Python

ML frameworks

Tools

UiPath

Azure AI tools

Visio

Lucidchart

Signavio

Bizagi

Job description

Tiger Analytics is seeking an AI Engineer to drive on-site deployment, integration, and scaling of enterprise Generative AI solutions. You will embed within customer engineering teams to operationalize LLMs and retrieval systems across Azure, bridging research and production.

You will collaborate with cross-functional teams to ensure business value and communicate outcomes. The role emphasizes hands-on automation engineering, SDLC adherence (Agile/Scrum), and working with modern ML/AI frameworks