Vaishnavi Veerkumar

About

AI engineer who built a production e-commerce system that analyzes product images alongside sales and demographic data to generate actionable creative recommendations, now used by 20+ clients. Also built orchestrated document/agent pipelines (Airflow, LangGraph) including a compliance drift detector auditing 401 compliance documents, with an emphasis on traceability, logging, and production integration.

Experience

Education

Key Strengths

• Built and deployed an AI-driven e-commerce image recommendation system from scratch serving 20+ clients
• Strong at diagnosing data issues (duplicate reference images) that caused generic model outputs and fixing via dataset cleanup
• Designed exclusion/filtering model to remove low-signal inputs (text-heavy images) to improve recommendation quality
• Hands-on orchestration experience (Airflow, LangGraph) for multi-stage pipelines and agent workflows
• Production reliability mindset: traceability from retrieval → trends extracted → prompt → output via robust logging
• Able to translate non-technical stakeholder needs into solvable AI problems and communicate outputs clearly

Reference Highlights

• Strong end-to-end ownership from research to production implementation
• Excellent cross-team collaboration
• Fantastic documentation
• Comes to meetings well-prepared with resources (links, docs)
• Proactive communication (asks for more use cases to test)
• Patient and clear with non-technical stakeholders
• Able to explain LLMs and prompting at a basic level
• Organized communicator
• Uses diagrams to clarify complex processes
• Well-paced verbal communication and invites questions
• Great attitude
• Effective with early adopters/customers
• Owned a computer-vision generative AI product end-to-end within the platform
• Strong at shipping AI products into production
• Strategic, data-driven approach to ambiguous problems
• Effectively integrates market insights, policy constraints, and technical experimentation
• Ensures output quality and diversity (not derivative results)
• Handled R&D to engineering/production transfer smoothly
• Proactive, constant communication across teams
• Creates validation sets to support engineering development and debugging
• Thorough preparation with many concrete examples for discussions
• Translates technical tradeoffs into business/strategy guidance for product managers