AI, Data & Technology - AI-ML Director

Grant Thornton US is building a market-leading AI practice focused on practical, secure, and scalable outcomes for our clients, and we are hiring AI/ML Solution Architects to lead discovery phase through production delivery. Hiring in most major US cities. As an AI-ML Architect you will translate business objectives into end-to-end AI architectures across ML/AI, application integration, data and governance—defining target-state designs, reference patterns, and implementation roadmaps; guiding technology choices across cloud and modern stacks; and partnering with security, risk, and delivery leaders to ensure solutions are operable, compliant, and measurable. The ideal candidate brings the right blend of hands-on AI engineering credibility and consulting leadership—strong communication with executives and technical teams, experience designing AI solutions that integrate with enterprise systems, and a pragmatic approach to tradeoffs across accuracy, cost, latency, reliability, and risk—along with the ability to mentor teams and shape repeatable assets and accelerators. We are actively recruiting for: Manager level (5+ years) for architects, and Director level (7+ years) for senior architects who can set technical standards, drive quality and reliability, and help shape reusable patterns and accelerators. This role is specifically a strategic investment to grow our AI capabilities and advisory services. If you want your work to matter, this is the moment: we are not building “another AI consulting practice”—we are rewriting the playbook for how clients deliver on the promise of AI. We’re building a practice where teams love the pace, the craft, and the real-world impact. Day-to-day responsibilities: Lead discovery workshops to clarify business objectives, constraints, and measurable success criteria for AI/ML initiatives Translate requirements into end-to-end target-state architectures across data, ML/AI, application integration, security, and governance Define pragmatic tradeoffs across accuracy, latency, cost, reliability, privacy, and risk—and communicate decisions to exec and engineering audiences Design the data + model lifecycle (pipelines, training/finetuning, serving, monitoring, drift detection, retraining) and the required MLOps/LLMOps foundations Establish integration patterns with enterprise systems (APIs/events/workflows, IAM, observability) so solutions are operable and supportable in production Partner with security, privacy, and risk teams to embed controls (access, auditability, data handling, responsible AI) into solution designs Produce core delivery artifacts (architecture diagrams, reference patterns, implementation roadmap, runbooks) and drive architecture reviews Mentor teams and build reusable assets/accelerators (reference architectures, templates, evaluation scorecards) to scale repeatable delivery quality You have the following technical skills and qualifications: Bachelor's degree preferably in data science or computer science or related discipline For managers, minimum five years of hands-on developer experience in machine learning and artificial intelligence stacks For Directors, at least two years of experience leading teams of AI/ML architects and developers Demonstrated experience designing and delivering production AI/ML solutions in an enterprise environment Strong grounding in cloud architecture (AWS/Azure/GCP), distributed systems, and modern data platforms Experience with MLOps practices (model lifecycle, monitoring, governance, deployment automation) Experience partnering with security/risk to implement privacy, access controls, auditability, and responsible AI practices Ability to lead senior client stakeholders through decisions under ambiguity Experience to develop long-standing relationships with clients Experience leading AI/ML delivery programs Experience with AI patterns (RAG, agentic, etc.) Preferred: experience with regulated environments (SOX, HIPAA, PCI, model risk management) Experience leading proposal solutioning / estimates / technical writing for pursuits Experience mentoring junior or senior colleagues in AI/ML architectures Experience guiding clients on build vs. buy decisions of AI/ML powered use cases Flexible, adaptable and an eager self-starter English: Fluent spoken and written communications skills Prior consulting industry experience or prior experience in an internal consulting role Consistent with the firm’s hybrid work model, this position will require in-person attendance at least two days a week either at a Grant Thornton office or at a client site Readiness to travel up to 60% Must be currently eligible to work in the United States, position is not eligible for employer sponsorship Consistent with the firm’s hybrid work model, this position will require in-person attendance at least two days per week, either at a Grant Thornton office or client site #Hybrid #LI-LG1 The base salary range for this position is between $170,568 and $274,554. Placement within the pay range is at Grant Thornton’s discretion, and it is based on multiple factors, including but not limited to, job -related knowledge/skills, experience, business needs, progression within the role, geographic location, and internal equity. At Grant Thornton, compensation decisions are dependent upon the facts and circumstances of each position and candidate.