Senior AI Engineer (Applied AI)

TL;DR

Senior AI Engineer (Applied AI): Design and deploy production-grade agentic AI systems that transform real-world workflows at scale with an accent on multi-agent systems, LLM integration, and data pipelines. Focus on building end-to-end AI pipelines from data ingestion through retrieval and orchestration, developing evaluation frameworks, and scaling infrastructure for high-stakes environments.

Location: Hybrid in San Jose, CA office. Must be authorized to work in the United States (no visa sponsorship available). Ability to commute to the office required.

Company

hirify.global is building the intelligence layer for global trade and logistics, turning fragmented, messy data into instant, reliable intelligence for AI in high-stakes environments.

What you will do

• Design and build multi-agent systems that reason across messy, real-world data
• Own end-to-end AI pipelines from data ingestion through retrieval, orchestration, and output
• Develop evaluation frameworks, benchmarks, and quality loops for reliability
• Build and scale data ingestion and retrieval infrastructure
• Integrate LLMs with enterprise data, tools, and workflows using frameworks like LangChain, LlamaIndex, Agno, and Semantic Kernel
• Ship full-stack product features in collaboration with end users and help define technical architecture and engineering culture

Requirements

• 4+ years hands-on software engineering; startup experience strongly preferred
• Proven track record shipping production-grade AI systems
• Strong experience with agent architectures, LLM systems, RAG pipelines, retrieval, grounding, and orchestration
• Strong Python proficiency and working knowledge of TypeScript
• 4+ years infrastructure experience (cloud, distributed systems); 4+ years with Docker and Kubernetes; 2+ years production LLMs
• Full-stack ownership mindset and strong data instincts for messy datasets

Nice to have

• Experience with evals frameworks and AI quality measurement
• Background in AI infrastructure or distributed systems
• Exposure to automotive, logistics, or physical-world domains
• MLOps/DevOps experience; CI/CD pipelines
• Former founder or early startup employee

Culture & Benefits

• High ownership, high impact, and bias for action in a small, sharp team
• Competitive compensation with equity participation
• Comprehensive medical, dental, and vision insurance
• Flexible time off
• Collaborative hybrid environment in San Jose headquarters