Builder - Operations (AI)

This role is the operational engine of the company, focusing on improving cross-functional efficiency, establishing GTM excellence, and managing the specialized resource and vendor pipeline for our core AI development.

Business Operations & GTM Excellence

• Process Design & Optimization: Design, implement, and maintain scalable operational systems and workflows to drive efficiency across Go-to-Market functions, including Sales, Marketing, and Customer Success.

• Operational Reporting & Metrics: Define, track, and analyze KPIs and operational throughput metrics. Translate complex data into clear, actionable insights for senior leadership decision-making.

• Data Analysis & Modeling: Serve as a self-sufficient analyst, leveraging tools (including SQL) to conduct ad-hoc analyses and build complex business models to evaluate the efficiency and cost-effectiveness of all GTM operations.

• Executive Support: Manage and deliver all executive-level reporting, financial modeling, and analytical support required for effective internal and external communication.

Strategic Operations & Program Management

• Operational Design for LLM Training: Design and manage the end-to-end operational program for training, fine-tuning, or augmenting proprietary Large Language Models, focusing on efficient workflow and quality gates. This includes designing the structured knowledge framework necessary for high-quality model grounding and Retrieval-Augmented Generation accuracy.

• Resource & Capacity Planning: Forecast the non-engineering resources (e.g., data labeling workforce, human feedback loops, specialized data acquisition) required for LLM training and set the operational cadence to meet technical roadmap timelines.

• Vendor & Tooling Management: Own the vendor selection, contracting, and performance management for external providers and specialized tools necessary for data collection, cleaning, and Human-in-the-Loop processes.

• AI Deployment & MLOps Strategy: Partner with Engineering to design the operational strategy for Machine Learning Operations, focusing on the seamless, scalable, and cost-effective deployment, monitoring, and updating of production AI models.

• Safety, Privacy, and Data Governance: Lead the operational governance of all AI data and model deployment. Implements all the required digital locks, guards, and tracking systems to keep sensitive AI data and user information secure and compliant with the law (e.g., GDPR, HIPAA, or specific domain regulations).

• LLM Knowledge Structure & QA: Oversee the quality assurance processes for structured data, ensuring the integrity and consistency of the LLM's knowledge base and classification systems to drastically reduce model drift and hallucination.

Qualifications & Skills

• Experience: 5-7 years in a high-impact strategic and operational role, such as Management Consulting, Corporate Strategy, or a high-growth startup's Business Operations team. (Bonus: Experience in an AI-native company, MLOps, or Data Governance).

• Project Leadership: Demonstrated ability to manage complex, resource-heavy programs (like the LLM training pipeline) and drive alignment across technical (Engineering/Data Science) and business teams. Must show competency in translating abstract data science goals into concrete, measurable operational workflows (e.g., data annotation and taxonomy design).

• Technical Fluency: Strong foundational understanding of ML/LLM training concepts (fine-tuning, RAG), data infrastructure (cloud platforms, databases), and operational deployment frameworks (MLOps).