AI Program Lead

Armada•Pittsburgh, PA

11d•Hybrid

About The Position

Exciting News – We’re Moving! As part of our continued growth and our commitment to fostering an exceptional, collaborative work environment, we’re thrilled to announce that our office will be relocating to a brand-new building at 2000 Innovation Drive, Wexford PA 15090 at the beginning of this year. In the meantime, hybrid employees will continue working from our current location at RIDC – O’Hara until the transition is complete. We’re excited about this next chapter and look forward to welcoming new team members to our growing organization! The AI Lead 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 Lead is expected to bring 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 five years of experience, with at least 2 in project/program management, facilitation, or leadership role.
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.

Nice To Haves

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 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