Principal AI Architect

Key Responsibilities: Define and own reference architectures for enterprise AI solutions, including model selection, model routing, retrieval, tool integration, orchestration, guardrails, observability, and evaluation. Lead the transition of AI prototypes into reliable, production-ready systems. Establish engineering standards covering architecture, code reviews, automated testing, quality gates, and release readiness. Design and implement solutions using open-weight AI models, including determining when fine-tuning provides advantages over hosted models. Lead model fine-tuning, training-data curation, evaluation, and production model serving. Optimize AI systems for cost, latency, scalability, and performance using techniques such as quantization, distillation, routing, caching, and batching. Build robust AI evaluation infrastructure, including offline evaluations, regression testing, CI/CD quality gates, online monitoring, and human review. Assess enterprise data readiness, governance, and technical feasibility before AI implementations begin. Lead and mentor a team of 30+ engineers and data scientists across multiple client engagements. Develop reusable AI architectures, frameworks, accelerators, and engineering best practices. Partner with sales and consulting teams on client workshops, proposals, technical due diligence, effort estimation, and solution design. Serve as the senior technical escalation point for architecture, performance, deployment, and production challenges.

Required Qualifications: 12+ years of experience across software engineering, architecture, data platforms, and AI/ML.Proven experience designing and deploying AI systems into production at scale using real enterprise data and users. Strong hands-on experience with open-weight models and production fine-tuning. Experience with full fine-tuning, LoRA, and/or QLoRA and the ability to evaluate models against baseline/frontier models. Demonstrated experience improving AI system cost and/or latency through model and infrastructure optimization. Strong understanding of AI evaluation and building evaluation infrastructure. Experience with enterprise data readiness, AI governance, and risk management. Working knowledge of NIST AI Risk Management Framework, ISO/IEC 42001, and EU AI Act risk tiers. Strong hands-on Python development experience. Experience with distributed systems, APIs, containers, Kubernetes, CI/CD, and GPU serving. Experience with at least one major cloud platform. Experience with platforms such as Databricks and/or Snowflake. Proven experience leading and mentoring senior engineering teams. Experience in a startup or product-company environment is preferred/required for the role. Bachelor's degree in Computer Science, Engineering, or a related technical field. We are an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex (including pregnancy, sexual orientation, or gender identity), national origin, citizenship status, age, disability, genetic information, protected veteran status, or any other characteristic protected by applicable law.https://www.e-verify.gov/sites/default/files/everify/posters/IER_RighttoWorkPoster.pdf