Senior AI Application Engineer (LLM)

TL;DR

Senior AI Application Engineer (LLM): Designing and building production-grade LLM integrations and AI-powered automation tools with an accent on RAG system design, API orchestration, and full-stack development. Focus on building scalable AI features, implementing observability, and ensuring security and compliance in AI systems.

Location: Must be based in the United States

Company

hirify.global is a SaaS platform that empowers creators to own their destiny by making first-party data accessible and actionable for personalized ecommerce experiences.

What you will do

• Architect and develop production-grade systems leveraging LLMs for internal automation and intelligent workflow assistance.
• Build scalable API integrations between AI models and internal systems like HRIS, CRM, and knowledge bases.
• Own end-to-end development of AI features from backend orchestration to frontend interfaces.
• Implement RAG and retrieval systems grounded in internal knowledge to ensure accuracy and relevance.
• Build and manage CI/CD pipelines for AI models, including evaluation frameworks and A/B testing.
• Instrument AI systems with observability tools for latency monitoring, hallucination detection, and cost management.

Requirements

• 3+ years of software engineering experience, with at least 2 years focused on building AI, ML, or LLM-powered systems in production.
• Deep expertise with LLMs (OpenAI, Anthropic, Mistral, Llama) and production API integration.
• Strong full-stack skills in Python (FastAPI/Flask/Django) and TypeScript/JavaScript.
• Experience with RAG systems, vector databases (Pinecone, Weaviate), and embedding models.
• Proficiency with cloud infrastructure (AWS/GCP/Azure), containerization (Docker/Kubernetes), and IaC (Terraform).
• Must be authorized to work in the United States.

Culture & Benefits

• Comprehensive health, welfare, and wellbeing benefits.
• Participation in annual cash bonus plans and equity programs.
• Supportive environment that values unique backgrounds and perspectives.
• Commitment to responsible AI use, privacy, and security.
• Opportunities to work on high-scale AI systems used by internal teams daily.