AI-ML Director

Grant Thornton (US)

AI-ML Architect responsible for translating business objectives into AI architectures. Leading delivery teams and mentoring in enterprise AI solutions development.

Posted 7/21/2026full-timePhiladelphia • Florida, Illinois, Massachusetts, Missouri, New York, North Carolina, Pennsylvania, Texas • 🇺🇸 United StatesLead💰 $170,568 - $274,554 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and delivering production AI/ML solutions, with a strong grounding in cloud architecture and MLOps practices. Capable of leading teams, mentoring colleagues, and establishing integration patterns while ensuring compliance with security and privacy standards.

Highest-signal resume keywords

AI/ML Solution DesignCloud Architecture (AWS/Azure/GCP)MLOps PracticesTeam LeadershipClient Stakeholder Engagement

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine LearningArtificial IntelligenceData Lifecycle ManagementArchitecture DesignModel MonitoringDeployment AutomationIntegration PatternsRisk ManagementTechnical WritingAI Patterns

Soft Skills

MentoringCommunicationAdaptabilityRelationship BuildingDecision-Making

Tools & Technologies

APIsIAMObservability ToolsData PlatformsArchitecture Diagrams

Industry Keywords

Enterprise EnvironmentRegulated Environments (SOX, HIPAA, PCI)Responsible AIAuditabilityPrivacy Controls

Tech Stack

Tools & technologies

AWSAzureCloudDistributed SystemsGoogle Cloud Platform

About the role

Key responsibilities & impact

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

Requirements

What you’ll need

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

Benefits

Comp & perks

Health insurance
401(k) matching
Flexible work hours
Paid time off
In-person attendance at least two days a week
Opportunities for professional development
Employee assistance program