What are the responsibilities and job description for the Director of Artificial Intelligence position at TalentPartners?
Director of Artificial Intelligence (AI)
Overview
A rapidly growing, innovation-driven telecommunications and fiber infrastructure company is seeking a Director of Artificial Intelligence (AI) to lead the development and execution of its enterprise-wide AI strategy.
This is a hands-on leadership role responsible for both designing and building AI capabilities from the ground up while also shaping the long-term vision for how AI transforms the organization. The Director will initially operate as an individual contributor, with a mandate to build and scale a high-impact AI team (4–5 members) over time.
The ideal candidate combines technical depth, business acumen, and execution capability, with a passion for leveraging AI to drive competitive advantage across customer experience, operations, and revenue growth.
Key Responsibilities
AI Strategy & Vision
- Define and lead the enterprise-wide AI roadmap aligned with business objectives
- Identify high-impact AI opportunities across:
- Sales & revenue generation
- Customer experience & personalization
- Customer service & support automation
- Network operations & infrastructure optimization
- Establish a framework for prioritizing AI initiatives based on ROI, feasibility, and scalability
Hands-On Development & Implementation
- Design, build, and deploy AI/ML models, tools, and workflows
- Develop prototypes and production-grade solutions across multiple business functions
- Work directly with data, systems, and engineering teams to integrate AI into core platforms
- Evaluate and implement modern AI technologies (LLMs, predictive models, automation tools, etc.)
Cross-Functional Leadership
- Partner with stakeholders across product, operations, IT, customer success, and sales
- Translate business challenges into AI-driven solutions
- Serve as the internal subject matter expert on AI capabilities and best practices
Team Buildout & Leadership
- Recruit, hire, and mentor a high-performing AI team (data scientists, ML engineers, etc.)
- Establish development standards, tooling, and processes for AI delivery
- Foster a culture of experimentation, speed, and measurable impact
Data & Infrastructure Enablement
- Assess and enhance data readiness, governance, and architecture to support AI initiatives
- Collaborate with engineering teams to ensure scalable and secure AI deployment
Innovation & Industry Leadership
- Stay ahead of emerging AI trends and technologies
- Position the organization as a leader in AI within the telecommunications and infrastructure space
- Identify opportunities to embed AI into core products and services
Qualifications
Required
- 8–12 years of experience in AI, machine learning, or data science roles
- Proven track record of building and deploying AI solutions in production environments
- Experience working in hands-on technical roles (not purely managerial)
- Strong programming experience (Python, ML frameworks, APIs, etc.)
- Experience with modern AI technologies including:
- Large Language Models (LLMs)
- Predictive analytics & machine learning
- Automation and AI-driven workflows
- Ability to operate as a builder and strategist simultaneously
Preferred
- Experience in telecommunications, infrastructure, SaaS, or technology-driven industries
- Experience building AI functions or teams from scratch
- Familiarity with customer-facing AI applications (chatbots, personalization, CX optimization)
- Exposure to network data, IoT, or infrastructure-related analytics is a plus
Key Attributes
- Builder mentality – thrives in a “0 to 1” environment
- Highly hands-on – comfortable coding, prototyping, and deploying solutions
- Business-minded technologist – connects AI initiatives directly to revenue and customer impact
- Entrepreneurial – operates with urgency, ownership, and creativity
- Collaborative influencer – able to drive adoption across non-technical teams
What Success Looks Like
- AI initiatives are deployed across core business functions within the first 6–12 months
- Measurable improvements in customer experience, operational efficiency, and revenue growth
- A high-performing AI team is built and delivering scalable solutions
- The organization establishes itself as an AI-forward leader in telecom infrastructure