AI, Data & Technology - AI-ML Architect

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

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.