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Bandreddy Sri Sai Lohith

Bandreddy Sri Sai Lohith

AI Engineer – LLM/RAG Payroll Risk Detection & Audit Automation

INDIA flag
Hyderabad, India
$10.00/hrIntermediateAws SagemakerGoogle Cloud Vertex AIInternal Proprietary Tooling

Key Skills

Software

AWS SageMakerAWS SageMaker
Google Cloud Vertex AIGoogle Cloud Vertex AI
Internal/Proprietary Tooling

Top Subject Matter

Payroll auditing
regulatory compliance
HR automation

Top Data Types

TextText
DocumentDocument
ImageImage

Top Task Types

Classification
Prompt Response Writing SFT
Segmentation
Entity Ner Classification
Polyline
Object Detection
Text Generation
Question Answering
Text Summarization
Fine Tuning
Evaluation Rating
Computer Programming Coding
Data Collection
Function Calling
Transcription
Bounding Box
Polygon
Cuboid
Point Key Point
RLHF
Red Teaming

Freelancer Overview

AI Engineer – LLM/RAG Payroll Risk Detection & Audit Automation. Brings 4+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Internal and Proprietary Tooling. Education includes Bachelor of Technology, Anurag University (2023). AI-training focus includes data types such as Text and labeling workflows including Classification and Prompt + Response Writing (SFT).

IntermediateEnglish

Labeling Experience

AI Engineer – LLM Prompt Engineering & Evaluation

TextPrompt Response Writing SFT
In this role, I created, evaluated, and curated prompts and expected responses for large language model pipelines within HR automation and payroll processing. My work included crafting high-quality prompt datasets, reviewing AI-generated outputs, and implementing improvements based on auditor and stakeholder feedback. I contributed substantially to the evaluation and continuous training of LLM models powering audit case processing and root-cause analysis. • Authored and tested prompts for RAG-enabled audit cases using structured and legal data inputs. • Evaluated and annotated model responses to ensure compliance, accuracy, and operational efficiency. • Partnered with product and compliance teams to refine model outputs and keep labeling tasks aligned with evolving business needs. • Deployed and leveraged AWS Bedrock and OpenAI for prompt engineering and model evaluation at scale.

In this role, I created, evaluated, and curated prompts and expected responses for large language model pipelines within HR automation and payroll processing. My work included crafting high-quality prompt datasets, reviewing AI-generated outputs, and implementing improvements based on auditor and stakeholder feedback. I contributed substantially to the evaluation and continuous training of LLM models powering audit case processing and root-cause analysis. • Authored and tested prompts for RAG-enabled audit cases using structured and legal data inputs. • Evaluated and annotated model responses to ensure compliance, accuracy, and operational efficiency. • Partnered with product and compliance teams to refine model outputs and keep labeling tasks aligned with evolving business needs. • Deployed and leveraged AWS Bedrock and OpenAI for prompt engineering and model evaluation at scale.

2023 - Present

AI Engineer – LLM/RAG Payroll Risk Detection & Audit Automation

TextClassification
As an AI Engineer at ADP, I led the architecture of LLM/RAG risk detection and anomaly analysis pipelines for auditing payroll records. My responsibilities included designing systems for automated data ingestion, rule definition in collaboration with compliance, and generating audit trails for each flagged case. I implemented and optimized AI models for payroll anomaly classification and root-cause analysis, training and evaluating model performance with ongoing auditor feedback. • Developed and maintained automated pipelines for ingesting and labeling structured payroll data and legal documents. • Defined and applied classification labels to time fraud, tax miscalculations, and duplicate payments, incorporating feedback from auditors for model improvement. • Built and tuned AI agents (LangChain) for high-precision anomaly detection, reducing false positives and manual review requirements. • Utilized internal/proprietary tooling integrated with AWS Bedrock, OpenAI APIs, and LangChain for large-scale data operation and model inference.

As an AI Engineer at ADP, I led the architecture of LLM/RAG risk detection and anomaly analysis pipelines for auditing payroll records. My responsibilities included designing systems for automated data ingestion, rule definition in collaboration with compliance, and generating audit trails for each flagged case. I implemented and optimized AI models for payroll anomaly classification and root-cause analysis, training and evaluating model performance with ongoing auditor feedback. • Developed and maintained automated pipelines for ingesting and labeling structured payroll data and legal documents. • Defined and applied classification labels to time fraud, tax miscalculations, and duplicate payments, incorporating feedback from auditors for model improvement. • Built and tuned AI agents (LangChain) for high-precision anomaly detection, reducing false positives and manual review requirements. • Utilized internal/proprietary tooling integrated with AWS Bedrock, OpenAI APIs, and LangChain for large-scale data operation and model inference.

2023 - Present

Education

A

Anurag University

Bachelor of Technology, Artificial Intelligence

Bachelor of Technology
2019 - 2023

Work History

A

ADP

AI Engineer & Software Engineer

Hyderabad
2023 - Present