Manager - Principal Technical Program, Development (51409)

Citrin Cooperman offers a dynamic work environment, fostering professional growth and collaboration. We’re continuously seeking talented individuals who bring a problem-solving mindset, fresh perspectives, and sharp technical expertise. We know you have choices, so our team of collaborative, innovative professionals are ready to support your professional development. At Citrin Cooperman, we offer competitive compensation and benefits and most importantly, the flexibility to manage your personal and professional life to focus on what matters most to you!

We are seeking a Manager – Principal Technical Program, Development, to join our Development team within the Information Technology department. As we develop our enterprise AI competency, we’re operating with two distinct but deeply connected workstreams: the foundation maintaining our core data platform (Data Operations), and the high velocity “Surge” initiatives industrializing applied AI and Agentic pilots (AI Solutions). You’ll serve as the critical bridge and strategic governor between these two worlds. 

This is a highly technical leadership role. You’ll bring deep expertise in enterprise data architecture to become the programmatic owner of our evolving data ecosystem. Your mandate is to ensure that our foundational data platform matures in lockstep with the rapidly changing, high-quality data product demands of advanced AI agents. You’ll oversee project portfolios across both Data Operations and AI Solutions, as well as manage external partners, resolve architectural bottlenecks, and owning the strict transition process that moves a successful AI pilot into a hardened, operationalized enterprise asset. The ideal candidate is a seasoned systems thinker who can seamlessly translate complex architectural vision into rigorous programmatic execution. 

Responsibilities are, but not limited to

• Programmatic Architecture Ownership: Serve as the strategic owner of the enterprise data architecture roadmap. Ensure that the foundational data platform (Microsoft Fabric) is evolving to meet the advanced data provisioning, latency, and quality requirements of Generative AI and multi-agent systems.

• The “Bridge” Coordination: Act as the essential point of synchronization between the Data Operations and AI Solutions teams. Prevent architectural silos by ensuring the “Fast Lane” (AI innovation) and the “Stable Lane” (Platform operations) are designing toward the same long-term enterprise standards.

• Transition & Operationalization: Own the end-to-end lifecycle of taking AI pilots to production. Define and enforce the strict criteria (security reviews, cost-per-token analysis, data governance, and LLMOps telemetry) required before an AI solution is permitted to transition from the build phase to long-term operations.

• SI & Vendor Governance: Manage the delivery of multiple System Integrator partners across both workstreams. Hold external teams strictly accountable to internal architectural standards, ensuring that “rapid prototyping” does not result in unmanageable technical debt.

• Intake, Triage & Prioritization: Establish a robust intake framework for new AI and data initiatives. Evaluate business requests, assess architectural feasibility, and route work appropriately to either the foundational platform queue or the applied AI surge team.

• Data Product Strategy: Champion the shift toward treating data as a product. Ensure that datasets exposed to Anthropic, OpenAI, or custom LangGraph agents are highly governed, standardized, and modeled for optimal retrieval (RAG) and reasoning.

The ideal candidate must:

• Have a bachelor’s degree in computer science, information technology, engineering, or equivalent practical experience. 
• Be Microsoft Certified: Fabric Data Engineer Associate (DP-700).
• Be Microsoft Certified: Azure AI Engineer Associate (AI-102).
• Have 10+ years of experience in technical program management, enterprise data architecture, or data engineering leadership within large-scale, complex organizations.
• Possess a deep, authoritative understanding of modern data architectures (e.g., Data Lakehouse, Data Mesh), cloud data platforms (Microsoft Fabric, AWS, Snowflake), and complex data pipeline orchestration.
• Have a proven track record of managing and delivering multi-million-dollar technology programs, particularly those involving hybrid internal teams and multiple external SI partners.
• Possess strong working knowledge of Generative AI infrastructure requirements, including RAG patterns, vector databases, and the specific data quality needs of non-deterministic models.
• Have demonstrated experience designing and enforcing transition frameworks (moving products from R&D/Innovation into enterprise IT operations).
• Be a stakeholder with exceptional management skills, capable of negotiating architectural trade-offs between C-level executives, specialized AI engineers, and operational infrastructure teams.
• Be a Strategic Governor: Bring a calming, organized authority to the inherent chaos of rapid AI innovation, enforcing discipline without stifling speed. 
• Be an architectural Pragmatist: Evaluate project success not just by on-time delivery, but by the long-term sustainability, security, and scalability of the underlying data architecture.
• Be an exceptional Translator: Be capable of bridging the communication gap between specialized AI researchers, traditional data engineers, and business-focused stakeholders.