Panith Chitturi

AI Engineer and Solutions Specialist with 2 years of experience designing, evaluating, and deploying enterprise Generative AI systems, prompt frameworks, and automated workflows. Experienced in translating complex business requirements into structured data logic, evaluating Large Language Model (LLM) output reliability, and building agentic pipelines. Proven ability to bridge technical engineering with stakeholder enablement to accelerate AI adoption across cross-functional teams.

Analyst, AI / LLM at Innodata (2025-12 – Present)

• Evaluate Generative AI and voice-agent outputs against strict accuracy, logic, and safety rubrics to enhance system reliability in production environments.
• Conduct systematic root-cause failure analysis on prompts and agent responses to resolve hallucinations, reasoning gaps, and formatting inconsistencies.
• Facilitate scoping discussions with project leads to convert operational business requirements into clear data logic, validation rubrics, and structured prompt guidelines.
• Design standardized evaluation datasets and regression test cases to support engineering teams during model updates and fine-tuning iterations.

Freelance at Independent AI & Solutions Consultant (2025-01 – 2025-11)

• Architected and deployed custom Generative AI applications and automated workflows for business teams using Gemini and OpenAI APIs.
• Developed interactive solution prototypes, including PRD generation engines and diagnostic prompt evaluation dashboards, to demonstrate enterprise AI feasibility.
• Researched and applied enterprise prompt governance frameworks, input sanitization methods, and guardrails to ensure deterministic model behavior.

AI Engineer at App Bezz Infotech (2024-06 – 2024-12)

• Collaborated with internal stakeholders to define technical requirements and establish secure API integration points connecting enterprise data with LLMs.
• Engineered and optimized structured prompt templates to increase task accuracy and minimize latency across core business workflows.
• Built and maintained automated data pipelines using REST APIs to ingest and structure multi-source business data for internal AI applications.

Bachelor of Engineering (B.E.) in Artificial Intelligence & Machine Learning – RNS Institute of Technology (VTU) (2024-06)