Manager - Principal AI Solutions Engineer, Development (51408)

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 AI Solutions Engineer, Development, to join our Development team within the Information Technology department. They act as the vanguard of our enterprise AI competency, as well as are responsible for transitioning successful Generative AI and Agentic pilots from rapid prototyping into scalable, secure production environments. They serve as the “Chief Technical Authority” for this transition.

In this highly strategic role, you’ll be the ultimate owner of our enterprise AI and Agentic design patterns. Operating initially as the “catcher’s mitt” for pilots developed by Partners, you’ll audit, refactor, and industrialize code to ensure it meets our rigorous standards for security, resiliency, and operational readiness. You’ll define how we build complex, stateful applications using frameworks (LangGraph), as well as how we interact with frontier models (Anthropic, Google, OpenAI).

Beyond immediate pilot industrialization, this is a cornerstone leadership role. As our AI competency matures, your career trajectory will evolve from establishing foundational standards to deploying as a hands-on “Technical Lead”, spearheading small, agile squads on future high-impact AI initiatives across the business. The ideal candidate is a pragmatic visionary—someone who can write flawless Python, debate cloud architecture, and confidently guide external partners toward enterprise-grade delivery.

Responsibilities are, but not limited to

• Agentic Pattern Ownership: Define, document, and enforce the enterprise standards for building AI agents. This includes standardizing state management (e.g., LangGraph), memory architecture, prompt versioning, and tool-use guardrails. 

• Governance & Code Industrialization: Act as the technical gatekeeper for all AI pilots built by partners. Conduct rigorous code reviews, refactor implementations as needed, and harden solutions for high-availability enterprise deployment. 

• Multi-Model Architecture Design: Architect dynamic routing and fallback strategies across multiple LLM providers (Anthropic, OpenAI, Google) to optimize cost, latency, and capability while avoiding vendor lock-in. 

• Evaluation & Telemetry Strategy: Own the technical approach to LLM evaluation. Establish the frameworks for tracking hallucination rates, token usage, drift, and agentic reasoning traces to ensure continuous quality monitoring in production. 

• Technical Leadership & Deployment: Serve as the technical anchor for the AI Solutions team. Mentor senior cloud and data engineers and prepare to deploy as the Lead Engineer / Squad Lead on future, highly complex AI product builds. 

• Cross-Functional Bridge: Partner closely with Data Operations, Software Engineering, Cloud Security, and Enterprise Architecture to ensure AI solutions seamlessly integrate with our broader Microsoft Fabric and cloud ecosystems. 

The ideal candidate must:

• Have a bachelor’s degree in computer science, information technology, engineering, or equivalent practical experience.
• Be Microsoft Certified: Azure AI Engineer Associate (AI-102).
• Have 8+ years of advanced software engineering, data architecture, or applied AI experience in complex, large-scale enterprise environments. 
• Have deep, hands-on programming expertise, particularly in Python, and strong familiarity with cloud ecosystems (AWS, Azure, and/or Microsoft Fabric). 
• Have eroven experience building and deploying generative AI applications, including deep knowledge of RAG architectures, vector databases, and multi-agent frameworks (LangChain, LangGraph, Semantic Kernel). 
• Have experience architecting solutions that interface with frontier models via API (OpenAI, Anthropic, Google Vertex AI). 
• Have demonstrated experience acting as a technical lead, including history of managing technical deliverables from external vendors or SI partners. 
• Have a strong background in building resilient, scalable systems with a deep understanding of CI/CD, Infrastructure-as-Code, and modern DevOps practices applied to non-deterministic systems (LLMOps). 
• Be a pragmatic Visionary: Deeply excited by the bleeding edge of AI, but ruthlessly practical about what it takes to run it safely in a production enterprise environment. 
• Be a high-Agency Leader: Does not wait for permission to establish standards. Steps into ambiguity, makes definitive architectural decisions, and rallies the team around them. 
• Possess diplomatic Authority: Capable of telling an SI partner “no” constructively, ensuring external builds align strictly with internal long-term maintainability. 
• Be a Teacher & Mentor: Actively focus on elevating the technical competency of the firm, freely sharing knowledge, and building up the engineers around them.