Staff Solutions Architect (AI)

TL;DR

Staff Solutions Architect (AI): Leads customer onboarding and implementation for AI Simulation solutions, focusing on establishing reference architectures and driving secure, reliable integrations across cloud/LLM/partner environments. Focus on accelerating customer adoption, improving platform operability, and shaping technical deployment standards for ML-based solutions.

Location: Remote (Canada or US). Compensation is tiered based on geographic location within the US, including major tech hubs (San Francisco, Los Angeles, Seattle, New York, Boston, Washington, DC) and other US locations.

Salary: CA$126,314 – CA$189,470

Company

hirify.global is a high-growth company leveraging AI solutions and Large Quantitative Models in life sciences, financial services, navigation, and cybersecurity, emerged from Alphabet Inc.

What you will do

• Lead customer onboarding and implementation for AISim Physics and ML-based solutions.
• Establish and maintain reference architectures, integration patterns, and implementation runbooks.
• Drive enterprise-grade deployment best practices for security, identity/access, networking, and observability.
• Serve as a technical advisor to Product and Engineering teams, contributing to platform improvements.
• Provide technical escalation support and root-cause analysis for durable fixes.
• Contribute to field motions including solution scoping and demos.

Requirements

• 7+ years of experience in Solutions Architecture, Customer Engineering, or Technical Consulting for enterprise SaaS, ML platforms, or data-intensive systems.
• Strong cloud architecture experience (AWS/Azure/GCP) including IAM, networking, compute, storage, containers/Kubernetes, and observability.
• Working knowledge of ML and data pipelines, including deployment, evaluation, monitoring, and governance.
• Proven ability to translate customer requirements into clear architectures and implementation plans.
• Excellent communication skills for both technical and executive stakeholders.

Nice to have

• Familiarity with LLM ecosystems (model APIs, RAG/agents, evaluation/monitoring).
• Experience with product-led growth enablement.
• Background supporting regulated or security-sensitive enterprise deployments.
• Exposure to scientific computing, life sciences, or materials sciences.

Culture & Benefits

• Work that directly accelerates discovery in drugs, materials, health, and sustainable technologies.
• Competitive base salary, performance-based incentives, and equity participation.
• Comprehensive medical, dental, and vision coverage, retirement savings with company matching, and paid parental leave.
• Fully remote with flexible paid time off and company-wide seasonal breaks.
• Opportunities for continuous learning, growth, and cross-functional collaboration.