Senior AI Software Engineer (AI)

TL;DR

Senior AI Software Engineer (AI): Design and ship production-ready software leveraging LLMs and Agentic AI workflows with an accent on integrating AI tools into the development lifecycle. Focus on building scalable systems, optimizing prompt engineering, and developing agentic coding techniques to accelerate delivery.

Location: Onsite in Sandy, UT, USA

Company

hirify.global is a global leader in cloud platforms for customer experience and contact center technology serving over 25,000 organizations worldwide.

What you will do

• Design, build, and ship software across the full development lifecycle.
• Implement AI coding tools and Agentic AI Workflows for code generation, testing, and debugging.
• Develop clean, production-quality code and specification documents using AI as a partner.
• Collaborate with product managers and designers to deliver working solutions.
• Apply prompt engineering to improve output consistency and accelerate development.
• Evaluate and adopt new AI tools to raise engineering standards across the team.

Requirements

• Solid experience in backend, frontend, or full-stack software development.
• Hands-on experience with AI coding tools and LLMs in real production environments.
• Practical knowledge of prompt engineering, agents, and AI-assisted workflow automation.
• Understanding of LLM constraints, including context windows, token costs, and latency.
• Proficiency in modern programming languages, APIs, and distributed systems.
• Location: Must be based in Sandy, UT, USA

hirify.global-to-have">hirify.global to have

• Experience in CX, contact center, or enterprise SaaS environments.
• Familiarity with CCaaS platforms, voice/chat AI, or customer-facing AI products.
• Exposure to building or tuning agentic systems or multi-step AI pipelines.
• Experience contributing to internal developer platforms or shared tooling.

Culture & Benefits

• AI-first culture that treats AI fluency as a professional standard.
• Access to modern AI tools, frameworks, and dedicated space for experimentation.
• High level of ownership and trust in decision-making from development to production.
• Culture of continuous improvement regarding both delivery and engineering processes.
• Clear growth paths into specialized engineering roles based on skill development.