AI Applications Engineer: Gen AI, LLMs & RAG Expert

Lancesoft; Phoenix (AZ); On-site; USD 110,000 - 170,000; Full time

Job summary

Lancesoft in Phoenix is seeking an experienced AI Applications Developer to identify, design, develop, and implement AI solutions that reduce admin workloads and streamline business processes. The role bridges business and technical teams, translating operational requirements into practical AI-driven solutions.

The candidate will have hands-on Python experience and expertise with Azure OpenAI, LLMs, and responsible AI practices, including architecture, testing, documentation, and deployment.

Qualifications

• Master's degree in Artificial Intelligence or a related field or equivalent hands-on AI development experience.
• 2+ years hands-on AI development experience and proven ability translating business needs into AI solutions.
• Experience with Generative AI, LLMs, and RAG architectures.
• Knowledge of AI governance, data privacy, security, and Responsible AI principles.

Responsibilities

• Gather and translate business requirements into technical specs for AI implementation.
• Evaluate enterprise AI platforms and determine build vs. buy options.
• Design, prototype, and deploy custom AI applications using Python and related tech.
• Develop Generative AI solutions with LLMs, Azure OpenAI, and enterprise platforms.

Skills

AI development

Generative AI

LLMs

Prompt engineering

RAG

Python

Architectural design

Testing

Documentation

Security governance

Education

Master's degree in Artificial Intelligence or related field

Tools

Azure OpenAI

GitHub Copilot

Vector databases

Embeddings

Job description

Lancesoft in Phoenix is seeking an experienced AI Applications Developer to identify, design, develop, and implement AI solutions that reduce admin workloads and streamline business processes. The role bridges business and technical teams, translating operational requirements into practical AI-driven solutions.

The candidate will have hands-on Python experience and expertise with Azure OpenAI, LLMs, and responsible AI practices, including architecture, testing, documentation, and deployment.