AI Engineer

Job Description

The client is building an AI Center of Excellence (CoE) from the ground up. As one of the first engineering hires in the CoE, you will be the technical engine behind every AI implementation the company runs, setting up the models, building the safety and reliability infrastructure, and establishing the engineering standards that every future AI project will inherit.

This is a greenfield role with high ownership. You will not be maintaining legacy systems, you will be designing and building the foundational AI platform that Hotwire's business units depend on. You'll partner closely with the Director of AI Implementation and AI Champions embedded in each business unit, translating validated workflow proposals into production-grade AI solutions.

PR: $70-$75/hr.

We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please send a request to View email address on click.appcast.io learn more about how we collect, keep, and process your private information, please review Insight Global's Workforce Privacy Policy:

Skills and Requirements

Engineering Foundation

• 4+ years of software engineering experience with a strong bias toward system design and production-grade architecture

• Expert-level Python, you write clean, tested, maintainable Python, not just scripts

• Deep understanding of API design, microservices patterns, async programming, and distributed system fundamentals

• Hands-on experience with CI/CD pipelines, containerization (Docker), and cloud-native deployment

• Strong debugging instincts, you can trace a failure from a user-facing symptom down to a model API edge case

AI / LLM Production Experience

• 2+ years building and operating production LLM applications, not prototypes, not demos, production systems with real users and real SLAs

• Experience deploying and managing LLMs on enterprise cloud platforms: Azure OpenAI Service or AWS Bedrock

• Proficiency with at least one LLM orchestration framework: LangChain, LangGraph, LlamaIndex, or equivalent

• Hands-on implementation of RAG (Retrieval Augmented Generation) pipelines from chunking strategy to retrieval tuning

• Direct experience implementing AI security controls: PII redaction, prompt injection defense, output filtering

• Familiarity with LLM evaluation approaches, you have built or operated an eval pipeline, not just read about it