Sr. Applied AI Engineer (AI)

TL;DR

Sr. Applied AI Engineer (AI/ML Ops): Building and evolving shared infrastructure and common foundations for AI and ML development across the company with an accent on LLM proxy servers, observability tooling, and ML Ops platform capabilities. Focus on improving how models are accessed, monitored, evaluated, and deployed in production to enable scalable and secure AI-powered workflows.

Location: Must be based in NAMER or EMEA

Salary: $191.5K – $287.3K

Company

hirify.global is an all-remote company focused on democratizing automation to make work more efficient and creative.

What you will do

• Build and evolve shared AI Platform capabilities for machine learning and generative AI.
• Improve LLM Ops and ML Ops capabilities, including observability, monitoring, and deployment workflows.
• Design systems to measure and improve performance, reliability, safety, and cost efficiency of AI experiences.
• Identify tooling gaps and standardize best practices for deploying and monitoring AI-driven features.
• Collaborate with product, infra, and data teams to ensure AI components are reusable and well-documented.
• Evaluate emerging AI tools, models, and patterns for incorporation into the shared platform.

Requirements

• 7+ years of experience in software engineering.
• 3+ years of experience building distributed, scalable, cloud-based ML/AI systems in production.
• 2+ years of experience in LLM Ops, ML Ops, or adjacent platform infrastructure work.
• Experience building shared services, internal platforms, or reusable developer tooling.
• Experience with the full lifecycle of building, testing, deploying, and scaling ML/LLM architectures.
• Proficiency in cloud infrastructure technologies; comfort with typed languages and modern backend practices.

Nice to have

• Experience with TypeScript and Python.

Culture & Benefits

• Fully remote work environment with a strong commitment to transparency and diversity.
• Competitive compensation including base salary, equity, and bonuses.
• Culture centered around democratizing automation and operational excellence.
• Guidelines provided for responsible and transparent AI usage during the hiring process.