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 – AI Technical Product, Development, to join our Development team within the Information Technology department. They’re responsible for pioneering our enterprise AI competency, as well as bridging the gap between fast-moving generative AI pilots and enterprise operations. They serve as our dedicated “Value & Transition Lead,” embedding directly alongside our System Integrator (SI) Partners and Subject Matter Experts (SMEs).

In this highly strategic role, you won’t dictate the daily development backlog, rather, you’ll ride shotgun with autonomous SI/SME pods to capture, quantify, and protect the value of their work. Your mandate is to act as the “Value Harvester”, by shadowing the development process to extract baseline evaluation datasets, documenting precise AI performance criteria, and championing the business ROI at every step. By front-running the transition process, you’ll ensure, long before a pilot project ends, that our internal operations team has a repeatable, standardized playbook for maintaining, monitoring, and scaling the AI solution across the enterprise.

Responsibilities are, but not limited to

1. Value Harvesting & Baseline Capture: Shadow autonomous SI teams and service-line SMEs during the pilot phase. Proactively extract and document the specific evaluation criteria, ground-truth datasets, and baseline performance metrics.
2. Transition Front-Running: Anticipate the operational needs of a pilot, long before it is finished. Engage InfoSec, Data Operations, and Enterprise Architecture early in the SI build process to clear roadblocks and ensure a frictionless handover to the support team.
3. Playbook Development: Author the definitive “Day-Two” operational playbooks. Translate pilot value characteristics into repeatable processes for capturing, baselining, monitoring, and responding to changes in AI value measures (e.g., token drift, accuracy degradation).
4. ROI & Performance Championing: Continuously monitor the agent’s performance against the originally stated SME value proposition. Ensure that the excitement of the “demo phase” translates into quantifiable, measurable business outcomes as the solution nears production.
5. Cross-Service Line Standardization: Observe disparate pilot workstreams across different business units and synthesize their varied evaluation methods into a single, cohesive enterprise standard that the Data Operations team can efficiently support.
6. Shadowing & Support: Act as a strategic partner to the SMEs, helping them articulate their evaluation criteria, while ensuring the SI understands any operational realities, of our environment, that may put value creation at risk.

The ideal candidate must:

1. Have a bachelor’s degree in computer science, information technology, engineering, or equivalent practical experience.
2. Have 5+ years of experience in Technical Product Management, IT Service Management (ITSM), or AI Strategy, with a focus on transitioning complex systems from R&D/external vendors into enterprise operations.
3. Possess deep familiarity with how System Integrators operate, including an understanding of the typical gaps between SI deliverables and operational readiness.
4. Possess strong conceptual understanding of Generative AI and agentic evaluation frameworks (e.g., LLM-as-a-judge, RAG precision/recall metrics) and the data required to establish performance baselines.
5. Possess exceptional technical writing and process design skills, with a proven track record of creating standardized operational playbooks for highly complex, non-deterministic systems.
6. Be highly autonomous and comfortable operating in a “matrixed” environment where you must influence and extract information from autonomous teams without having direct command-and-control authority over their daily tasks.
7. Be a “Day-Two” Thinker: While everyone else is excited about the initial pilot launch, you are obsessively focused on how the system will be monitored and maintained six months later.
8. Be a diplomatic Extractor: Possess the emotional intelligence to embed with fast-moving SI/SME teams, supporting their autonomy while firmly extracting the rigorous documentation and datasets the enterprise requires.
9. Be a synthesizer: Sit in a room full of highly technical AI engineers and business-focused SMEs, translate the conversation, and distill it to address product operations.

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