AI Product and Platform Head

About CLOUDIT

CLOUDIT is a US-registered LLC specializing in delivering expert accounting and consulting services to small and medium-sized accounting firms throughout North America. Its India office focuses on creating bespoke back-office operations designed to enable US-based accounting firms to confidently manage and grow their practices. The company leverages cutting-edge technologies and client-focused back-office support solutions to offer unparalleled accounting services, staffed by a team of qualified professionals committed to building a world-class accounting service provider.

Role Overview and Responsibilities

• Define and lead the overall product vision, roadmap, and execution strategy, ensuring all decisions are driven by an output-versus-outcome mindset.
• Convert the four-stage workflow and Fiverr-like "Submitted, Needs Correction, Accepted" model into seamless, user-friendly processes for clients, the internal CLOUDIT team, accounting firms, and management.
• Apply strict prioritization by delivering a minimal viable product first, followed by a phased expansion.
• Architect and implement an AI platform serving as an orchestration layer that routes prompts to various Large Language Models (LLMs) such as ChatGPT, Claude, Gemini, Grok, and Perplexity via a unified interface.
• Design the Retrieval-Augmented Generation (RAG) framework, including ingestion, embeddings, vector storage, and retrieval mechanisms that ensure business-specific and precise prompt answers.
• Develop prompt-routing strategies with guardrails and fallback plans to optimize quality, speed, and cost, avoiding dependence on any single vendor.
• Create token usage metrics and an AI-hour billing model that combines token costs, margins, and human labor costs.
• Construct and integrate workflow layers combining AI outputs with human validation across four phases: Pre-Processing, CLOUDIT Review, Firm Review, and Client Output.
• Implement features such as satisfaction and need for human validation branches, task-level messaging (including archived chats), document-output toggles, and consultation booking flows.
• Establish time tracking for AI activities, human review, and calls at designated rates.
• Develop client-specific knowledge systems by normalizing diverse data sources (e.g., ERP/accounting systems, POS, CRM, spreadsheets, meeting notes, employee knowledge) into unified datasets per client.
• Build and sustain integrations/connectors with popular accounting, ERP, and POS platforms.
• Define protocols for updating and enhancing the knowledge base continuously as new client data is collected.
• Lead and mentor engineering, data, and AI teams, setting technical standards and workflows.
• Oversee product delivery by managing agile processes, scope, dependencies, and ensuring timely, quality releases.
• Make practical build-versus-buy and architectural decisions, while maintaining a technical risk register.
• Collaborate across operations, partner firms, and clients to align the product with real workflows.
• Facilitate multi-party collaboration tools such as firm-branded emails, in-app communications, notifications, reminders, VOIP with call recording, and transcripts accessible to firm owners.
• Partner with leadership on pricing strategies, go-to-market plans, and rollout decisions.
• Monitor AI output accuracy, establish quality measurement, review processes, and continuous improvement.
• Ensure system performance, security, and reliability, including features like encrypted credential vaults, role-based access controls, and comprehensive audit logging.
• Track and optimize AI token cost and infrastructure spending relative to revenue and margins.
• Drive minimum viable product (MVP) development toward a live, fully functioning task with one pilot firm and client.
• Manage pilot testing, gather feedback, validate billing with real invoice samples, and apply insights to rollout planning.

Preferred Candidate Profile

• Demonstrated experience in SaaS product development from inception to scaled production.
• Hands-on expertise with AI/ML systems including LLMs, RAG, embeddings, vector stores, and AI workflow implementation.
• Strong knowledge of API design, cloud infrastructure, and contemporary data systems architecture.
• Ability to translate complex, unstructured business workflows into efficient technical solutions.
• Proven leadership in managing cross-functional engineering teams with decisiveness and clarity.
• Effectiveness in delivering MVPs and rapid iteration under strict deadlines.
• Bachelor’s degree in Information Technology or equivalent engineering discipline required.