ROHAN PAMIDIMUKKLA

AI Engineer / Technical Lead

• Led the end-to-end re-architecture of Clara, a production customer support agent, during a critical outage of OpenAI services. Delivered a modular multi-agent solution using LangGraph—a first at this scale within the company—ensuring business continuity under high pressure.
• Engineered plan-and-execute supervisors with specialized subagents, enabling subject matter expertise routing, which reduced customer response latency by 4 seconds and cut token usage by 43%.
• Technical Lead for Mission Control, a high-visibility AI orchestration framework acting as a super-agent, built using the ADK framework and Teams Agent Toolkit, enabling intelligent routing across organizational agents.
• Pioneered API-based agent deployments in GCP, setting a new enterprise standard for agent deployment at NRG, and successfully presented results to the CIO under an aggressive timeline.
• Collaborated cross-functionally with data science, product, and engineering teams to align technical AI solutions with business strategy and reporting needs.
• Continuously iterated on GenAI pipelines, focusing on RAG, prompt tuning, and agentic design, using tools like Python, PyTorch, and GCP Cloud AI services.
• Practiced strong DevOps/MLOps principles, leveraging Azure Devops, Git, Docker, and CI/CD pipelines for scalable, maintainable AI deployment workflows.

Project 1 – Project Astro Project 2 – Sparkle Data Platform Modernization & Reporting

Lead – Enterprise LLM Solutions

• Spearheading the development of custom Large Language Model (LLM) solutions tailored for enterprise use in high-security environments.
• Conducted deep experimentation and super fine-tuning of various models including BERT, FLAN-T5, LLaMA, and Azure OpenAI, optimizing them for domain-specific tasks.
• Pioneering a Natural Language to ML Pipeline interface that enables non-technical users to access, query, and perform predictive analytics entirely through natural language.
• Continuously driving innovation on the Astro platform, aligning cutting-edge AI capabilities with enterprise usability and security standards.

Lead – Apache Spark Optimization & ML Integration

• Leading a new initiative to design an Apache Spark Compute Resource Optimizer, targeting large-scale performance gains and cost efficiency in Databricks.
• Achieved ~60% performance improvement through horizontal hyperparameter tuning and runtime environment adjustments.
• Engineered a custom codebase parser, Scala-based log retrieval library, and a logical test block algorithm to better monitor and optimize Spark workloads.
• Currently advancing the project toward full automation via reinforcement learning, aiming for a self-sufficient, cost-minimizing system capable of dynamically adapting to new codebases and workloads.

Data Engineer / Cloud Migration Specialist

• Partnered with stakeholders to redefine business data strategy, leading the full-scale migration of legacy infrastructure to the Azure Cloud ecosystem.
• Designed and deployed hundreds of Azure Data Factory pipelines, architected complex SQL stored procedures and views, and modernized enterprise-wide reporting workflows.
• Delivered 15+ Power BI reports by modeling data directly from SQL Server Data Warehouses, enabling enhanced insights and decision-making across departments.
• Streamlined and automated data flows, significantly reducing report latency and improving data reliability.

• Contributed to the core product development team of a high-growth unicorn startup, actively participating in the enhancement of a live, customer-facing platform.
• Delivered new product features and improvements using C#, JavaScript, and SQL, collaborating closely with cross-functional teams.
• Spearheaded bug fixes and implemented quality-of-life improvements that enhanced user experience and system stability in the AWS cloud environment.
• Took part in multiple high-impact projects, including feature rollouts and Point of Sale (POS) system integrations, helping accelerate product delivery timelines.