Senior Site Reliability Engineer (AI)

Location: Hybrid, requiring 3 days per week in office in the New York City or Boston metro areas; applicants in the Research Triangle or San Francisco Bay Area may also be considered. Candidates must reside in these locations or be willing to relocate.

Total compensation range: $185,500–$232,000 per year, plus equity, benefits, and perks.

Company

hirify.global is an AI-driven pharmaceutical company developing technology platforms and capabilities to accelerate drug development and clinical trials.

What you will do

• Own the infrastructure and operational platform for shared engineering workloads, including compute, orchestration, deployment, observability, access controls, and reliability.
• Build and operate secure infrastructure for product applications, containerized services, internal tools, data systems, ML pipelines, inference, and agentic software.
• Develop and maintain AWS infrastructure across development, staging, and production, including networking, databases, load balancers, and secrets management.
• Create and optimize infrastructure as code, CI/CD pipelines, and reusable platform patterns.
• Establish SLOs, monitoring, alerting, runbooks, incident response, diagnostics, root cause analysis, and post-incident practices.
• Partner with Product Engineering, Data Engineering, and Data Science while mentoring engineers on infrastructure and SRE fundamentals.

Requirements

• 5+ years of experience in Site Reliability Engineering, infrastructure, systems, DevOps, or a similar discipline.
• Production experience operating cloud infrastructure and distributed systems with strong reliability judgment.
• Experience with advanced diagnostics, incident response, root cause analysis, observability, and automation.
• Experience with AWS and Snowflake.
• Working experience with Docker, GitHub, Kubernetes, Python, Terraform or OpenTofu, and virtual networking.
• Daily fluency with AI tools, including LLMs and agentic coding systems, with strong judgment for validating their output.

Nice to have

• Experience with Azure, GCP, Vercel, or Terragrunt.
• Experience supporting production ML or AI workloads, MLOps infrastructure, workflow orchestration, or model serving.
• Experience operating infrastructure in a regulated or validated environment.

Culture & Benefits

• Hybrid work model with three office days per week.
• Equity and comprehensive benefits.
• Generous perks.
• Opportunity to use AI tools in daily engineering practice and shape AI-native engineering systems.