Senior Staff AI Engineer (AI)

TL;DR

Senior Staff AI Engineer (AI): Designing, evolving, and scaling enterprise AI platforms including agentic AI, LLM platforms, and RAG with an accent on architecture-level decisions and platform strategy. Focus on building scalable, secure AI orchestration frameworks, solving complex distributed systems challenges, and ensuring reliability in production-grade AI services.

Location: Remote (USA)

Salary: $199,500 - $299,300 Annually

Company

hirify.global builds the most complete cloud analytics and data platform for AI to empower enterprises to make confident, data-driven decisions at scale.

What you will do

• Lead the design and evolution of large-scale distributed AI systems and AI-native products.
• Own end-to-end architecture for agentic workflows, RAG pipelines, vector search, and AI orchestration frameworks.
• Develop production-grade AI systems using LLMs, embeddings, and agent-based architectures.
• Implement guardrails for reliability, safety, governance, and cost control in enterprise AI systems.
• Partner with product, architecture, and research teams to translate business requirements into scalable AI solutions.
• Mentor senior and staff engineers to raise the overall technical bar across the organization.

Requirements

• Bachelor’s degree in Computer Science, Engineering, or equivalent practical experience.
• 12+ years of experience building backend services, distributed systems, or data/AI platforms.
• Strong proficiency in Java, Go, or Python for building large-scale services.
• Deep understanding of distributed system design, scalability, and cloud-native architectures.
• Proven experience operating production systems with SQL and NoSQL data stores.
• Must be based in the US to be eligible for corporate benefits and payroll.

Nice to have

• Experience with LLMs, embeddings, vector databases, and AI orchestration frameworks.
• Exposure to agentic AI patterns such as tool calling, planning, and multi-step reasoning.
• Experience building AI systems in cloud environments (AWS, Azure, or GCP).
• Familiarity with Kubernetes, Docker, and CI/CD pipelines.

Culture & Benefits

• Flexible work model based on trust and autonomy.
• Comprehensive benefits including healthcare, life, and disability insurance.
• 401(k) retirement savings plan.
• Dedicated time-off programs.
• Inclusive environment that celebrates diversity and people-first culture.