Staff AI Solutions Engineer (AI)

TL;DR

Staff AI Solutions Engineer (AI): Building and deploying bespoke AI-powered solutions and scalable workflows across the organization with an accent on LLM integration, RAG architectures, agentic workflows, and AI enablement. Focus on translating ambiguous business requirements into production systems, evaluating build-versus-buy decisions, and enabling teams through training, office hours, and hackathons.

Location: Hybrid role based in the United States, with an expectation to work from a hirify.global office at least three days per week. Hub locations are San Francisco, Denver, and Nashville in the United States, with an additional hub in Santiago, Chile. A relocation stipend may be available for relocation to a hirify.global hub location.

Salary: $177,000–$208,000 USD base salary or on-target earnings range for San Francisco, California.

Company

hirify.global builds an AI-powered data platform for safe and fair verification and decision-making used by companies and individuals.

What you will do

• Gather requirements from departments and translate workflows and business needs into technical AI solutions.
• Evaluate, configure, and recommend AI tools and platforms, including build-versus-buy decisions.
• Design, develop, and deploy custom solutions using LLMs, RAG architectures, agentic workflows, and automation frameworks.
• Architect reusable AI workflow templates, playbooks, prompt libraries, reference architectures, and self-service resources.
• Run AI office hours, hackathons, workshops, training sessions, and product demonstrations.
• Partner with engineering, business systems, security, and data engineering teams on secure, compliant, and scalable AI adoption.

Requirements

• Bachelor’s degree in Computer Science or equivalent experience.
• 5+ years of experience in engineering, solutions engineering, or technical enablement, including measurable productivity improvements.
• 3+ years of hands-on experience developing AI-centric products and solutions involving machine learning, generative AI, LLMs, RAG, agentic frameworks, and prompt engineering.
• Deep proficiency in Python and experience integrating LLM models into applications and using cloud platforms such as AWS, GCP, or Azure.
• Experience leading enablement programs, gathering requirements from non-technical stakeholders, and creating scalable documentation and training resources.
• Strong communication, presentation, problem-solving, solution architecture, production coding, and workshop facilitation skills.

Culture & Benefits

• Fast-paced, collaborative work environment with a strong focus on in-office collaboration.
• Learning and development allowance.
• Competitive cash and equity compensation with advancement opportunities.
• 100% medical, dental, and vision coverage.
• Flexible PTO, monthly wellness stipend, and up to $25,000 reimbursement for fertility, adoption, and parental planning services.
• In-office perks include lunch, commuter stipend, snacks, and beverages.