AI-ML Director

• 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

• 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

Core Competencies

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 Design
• Cloud Architecture (AWS/Azure/GCP)
• MLOps Practices
• Team Leadership
• Client Stakeholder Engagement

ATS Optimization Keywords

Hard Skills

• Machine Learning
• Artificial Intelligence
• Data Lifecycle Management
• Architecture Design
• Model Monitoring
• Deployment Automation
• Integration Patterns
• Risk Management
• Technical Writing
• AI Patterns

Soft Skills

• Mentoring
• Communication
• Adaptability
• Relationship Building
• Decision-Making

Industry Keywords

• Enterprise Environment
• Regulated Environments (SOX, HIPAA, PCI)
• Responsible AI
• Auditability
• Privacy Controls

Tools & Technologies

• APIs
• IAM
• Observability Tools
• Data Platforms
• Architecture Diagrams