AI Software Engineer

TL;DR

AI Software Engineer (AI/Infrastructure): Building and scaling autonomous AI agents and agentic development workflows for enterprise data infrastructure with an accent on production-grade reliability, tool-calling, and evaluation frameworks. Focus on designing agentic IDE workflows, implementing MCP tooling, and ensuring operational readiness for high-scale production AI systems.

Location: Must be based in the United States. The role operates in a hybrid environment with in-office expectations.

Salary: $170,000–$253,000 USD

Company

hirify.global is a global leader in intelligent data infrastructure, providing unified storage and data services for multicloud and AI environments.

What you will do

• Drive spec-driven, agentic-IDE development workflows across the engineering organization.
• Design and ship production-ready AI agent workflows that automate complex toil.
• Build and maintain shared MCP tools and integrations for enterprise systems.
• Define quality gates and evaluation frameworks for AI-assisted code and production agents.
• Implement guardrails, monitoring, and rollback paths for AI agents in production.
• Design systems for operational readiness, including handling usage spikes and incident triage.

Requirements

• Must be based in the United States.
• Bachelor's degree in Computer Science, Engineering, or equivalent experience.
• 8+ years of professional software development experience with end-to-end system ownership.
• Production experience with LLMs, prompt engineering, and agent evaluation frameworks.
• Hands-on proficiency in Python, Go, or Java.
• Experience with orchestration frameworks like LangChain or LangGraph and MCP standards.

Culture & Benefits

• Comprehensive benefits package including health, life, and disability insurance.
• Retirement and pension plans with company contributions.
• Employee stock purchase plan and restricted stock units (RSUs).
• Flexible work environment balancing professional and personal life.
• Collaborative culture focused on innovation and data-driven impact.