Staff Software Engineer (AI)

TL;DR

Staff Software Engineer (AI): Leading the technical direction and architecture of hirify.global's ML platform infrastructure with an accent on low-latency model inference, large-scale feature stores, and LLM orchestration. Focus on driving cross-team technical initiatives, mentoring senior engineering talent, and scaling ML development velocity across the organization.

Location: Must be based in or able to work from South San Francisco or Seattle

Salary: $224,000 - $336,000

Company

hirify.global is a global financial infrastructure platform that processes billions in payments volume, enabling businesses to grow their revenue and accelerate new opportunities.

What you will do

• Own end-to-end architecture and system design for complex, high-impact ML platform projects.
• Define long-term technical strategy for next-generation ML infrastructure, including LLM and agentic AI patterns.
• Collaborate with ML engineers, data scientists, and product teams to translate business needs into scalable technical solutions.
• Arbitrate critical technical decisions balancing latency, reliability, cost, and security constraints.
• Mentor and grow engineering talent while serving as a role model for operational excellence.
• Represent the engineering organization to senior leadership regarding the end-to-end ML lifecycle.

Requirements

• 10+ years of professional software development experience in service-oriented architecture and large-scale distributed systems.
• Proven track record as a technical lead for multi-team initiatives.
• Experience working on production ML platform services.
• Strong product instincts and ability to operate in ambiguous environments.
• Excellent communication skills for both technical and non-technical stakeholders.
• Must be authorized to work in the US.

Nice to have

• Experience building large-scale serving or data infrastructure (e.g., feature stores, model registries).
• Familiarity with LLMs, agentic AI patterns, and RAG.
• Experience with cloud-based AI/ML services like SageMaker, Bedrock, or Databricks.
• Background in training and shipping production ML models.

Culture & Benefits

• Opportunity to work on infrastructure processing over $1.9T in annual payments volume.
• High level of autonomy and responsibility in a fast-paced, mission-driven environment.
• Collaborative culture working with cross-functional teams of data scientists and product engineers.
• Focus on technical excellence and solving complex, large-scale engineering challenges.