Senior Architect (AI Engineering and Platforms)

Location: Chicago, Illinois; hybrid, with regular virtual and in-person work at an assigned hirify.global office for a minimum of two days per week. Other location: Reston, Virginia. United States.

Salary: $142,500–$237,500 annually, with potential eligibility for annual bonuses and other incentives.

Company

hirify.global provides technology and data solutions and develops products and platforms for customers and internal users.

What you will do

• Shape the technical vision, architecture, and delivery of foundational AI platform capabilities across multi-cloud and hybrid environments.
• Build standardized development paths for AI-enabled products, including agentic AI, observability, evaluations, measurement, operational controls, and guardrails.
• Ensure platform availability, performance, scalability, security, data governance, metadata management, data quality, and compliance.
• Translate business and technical requirements into platform designs and delivery plans with cross-functional teams.
• Evaluate and integrate emerging technologies, provide technical guidance, conduct design reviews, and mentor engineers.
• Advance automation, DevOps, continuous integration, and continuous deployment for data and AI services.

Requirements

• Bachelor’s or master’s degree in Computer Science, Engineering, or a related field, or equivalent practical experience designing and delivering complex AI, data, or platform solutions.
• 10+ years of experience across ML engineering, data engineering, distributed systems, or platform development, including 3+ years of hands-on experience building GenAI platforms or capabilities.
• Hands-on experience delivering production GenAI solutions for internal or external users, including retrieval quality, latency management, cost optimization, and evaluation-driven quality improvements.
• Experience building scalable AI or data platform components adopted by multiple teams with measurable developer or user experience outcomes.
• Strong problem-solving, analytical, communication, and collaboration skills, including the ability to explain complex technical concepts to technical and nontechnical audiences.
• Advanced expertise in at least one major cloud platform: AWS, Azure, or GCP; working knowledge of multi-cloud and hybrid architectures.
• Strong proficiency with Docker, Kubernetes, infrastructure-as-code, API design, microservices, continuous integration, and continuous deployment.
• Hands-on knowledge of GenAI architecture and engineering, including vector search, knowledge graphs, RAG, agentic frameworks, model fine-tuning, evaluation frameworks, and cost management.
• Experience with distributed computing such as Apache Spark or Apache Hadoop; infrastructure-as-code tools such as Terraform or AWS CloudFormation; cloud security and compliance controls; and observability tools including Prometheus, Grafana, and the ELK Stack.

Nice to have

• Experience establishing standardized development patterns or “golden paths” for AI-enabled products.
• Familiarity with metadata management, data governance, and data quality frameworks.
• Experience optimizing AI platforms for retrieval quality, latency, reliability, and cost.
• Experience evaluating and integrating emerging AI technologies into enterprise-scale platforms.
• Experience providing technical mentorship and influencing engineering practices across multiple teams.

Culture & Benefits

• Hybrid work with flexibility and work/life support.
• Medical, dental, vision, HSA, and FSA options with day-one eligibility.
• Paid parental leave, caregiver support, adoption assistance, fertility planning coverage, and dependent-care benefits.
• 401(k) with employer match, ESPP, tuition reimbursement, career coaching, and financial wellness resources.
• Paid time off, up to 12 paid holidays, disability coverage, life insurance, wellness support, and employee assistance resources.
• Equal opportunity employment and consideration of qualified applicants with arrest or conviction records in accordance with applicable law.