AI Solutions Leader

ARMADA Supply Chain Solutions • Pine Township, PA

1d • Hybrid

About The Position

The AI Solutions Leader is responsible for driving meaningful business value from AI at Armada. This role focuses on partnering with business leaders to identify high-value problems to solve with AI, shaping feasible approaches, and leading delivery in an environment where clarity emerges through iteration. The AI Solutions Leader is expected to bring previous experience, strong opinions, technical judgment, and the credibility to push back on ideas that are unlikely to deliver value or succeed in practice. This role serves as the lead for Armada’s AI program, ensuring AI initiatives are intentionally prioritized, coordinated, and measured as part of a broader roadmap rather than executed as disconnected efforts.

This is a leadership role that blends technical understanding, stakeholder management, and delivery discipline. It is not a heavy programming role, but it does require deep understanding of how different AI approaches work and when they should (or should not) be used. AI solutions should be built pragmatically, leveraging the Microsoft ecosystem and off-the-shelf tools where appropriate, while avoiding unnecessary complexity or one-off implementations that won’t scale with a small team.

Requirements

• Bachelor’s degree in computer information systems or related field and/or proven knowledge & skill in AI, ML, and analytics.
• Minimum 7 years of experience, with at least 3 in product management, facilitation, or leadership role.
• Deep Expertise in AI-driven customer service solutions.
• Recent experience working with Azure, Fabric, and Power Platform.
• Ability to analyze complex technical and management problems and determine the most cost-effective solutions.
• Comprehensive knowledge of business practices and procedures, financial systems and controls, computer skills, and financial analysis techniques.
• Demonstrated ability to establish and maintain effective working relationships, to communicate clearly orally and in writing, and to influence when incumbent has no formal authority.
• Ability to communicate effectively with executive management and other senior level professionals.
• Strong business acumen, with the ability to understand business objectives, operational constraints, and decision-making contexts, and translate them into applied AI initiatives.
• Experience leading end-to-end AI or data-driven initiatives in a cloud-based environment, accounting for considerations such as: Value realization and ROI measurement, Cost awareness and optimization, Security and access controls, Data privacy and responsible AI considerations, Monitoring solution health, adoption, and effectiveness, Governance around data usage, AI outputs, and decision support
• Strong understanding of applied AI approaches, including: AI agents and copilot, LLM-based automation, classification, and reasoning, Proven expertise in traditional ML concepts (training, inference, evaluation, drift), Computer vision fundamentals (where applicable)
• Experience shaping and prioritizing work across multiple initiatives, including: Defining roadmaps and sequencing work, Establishing success metrics prior to delivery, Evaluating tradeoffs across value, feasibility, and risk
• Familiarity with the Microsoft analytics and AI ecosystem, such as: Microsoft Fabric, Copilot Studio and Power Automate, Azure-based data and AI services (at a conceptual and architectural level)
• Ability to work effectively with technical teams and partners
• Leading and guiding developers without needing to write production code
• Collaborating with internal teams or external partners for advanced modeling or analytics

Responsibilities

• Lead AI initiatives from idea to outcome
• Partner with stakeholders to clarify decisions, workflows, and constraints
• Shape ambiguous problems into solvable AI initiatives
• Maintain focus on measurable value, not experimentation for its own sake
• Define and evolve the Applied AI roadmap
• Establish near- and medium-term priorities aligned to business value
• Balance quick wins with longer-term capability building
• Adjust direction as business needs, data readiness, and technology evolve
• Apply sound judgment across AI approaches
• Evaluate and select between: AI agents and copilots, LLM-driven automation and reasoning, Computer vision, Traditional ML and data-driven techniques
• Avoid forcing AI where simpler solutions are more effective
• May have 1-5 direct reports, including AI developers, data engineers, or analysts.

What This Job Offers

• Job Type: Full-time
• Career Level: Manager