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AI Engineer with 4+ years of experience building machine learning, generative AI, and data-driven solutions. Skilled in Python, SQL, PyTorch, TensorFlow, and cloud platforms, with hands-on experience across RAG, semantic search, and LLM-powered workflows. Experienced in scalable AI pipelines and MLOps using AWS, Docker, Kubernetes, MLflow, Airflow, and FastAPI. Specialized in AI automation and agentic AI, including multi-agent systems and orchestration using LangGraph, CrewAI, AutoGen, and MCP servers.…AI Engineer with 4+ years of experience building machine learning, generative AI, and data-driven solutions. Skilled in Python, SQL, PyTorch, TensorFlow, and cloud platforms, with hands-on experience across RAG, semantic search, and LLM-powered workflows. Experienced in scalable AI pipelines and MLOps using AWS, Docker, Kubernetes, MLflow, Airflow, and FastAPI. Specialized in AI automation and agentic AI, including multi-agent systems and orchestration using LangGraph, CrewAI, AutoGen, and MCP servers.

Gandham Harika

AI Engineer, Data Engineer, Software Engineer, +2

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AI Engineer with 4+ years of experience building machine learning, generative AI, and data-driven solutions. Skilled in Python, SQL, PyTorch, TensorFlow, and cloud platforms, with hands-on experience across RAG, semantic search, and LLM-powered workflows. Experienced in scalable AI pipelines and MLOps using AWS, Docker, Kubernetes, MLflow, Airflow, and FastAPI. Specialized in AI automation and agentic AI, including multi-agent systems and orchestration using LangGraph, CrewAI, AutoGen, and MCP servers.…AI Engineer with 4+ years of experience building machine learning, generative AI, and data-driven solutions. Skilled in Python, SQL, PyTorch, TensorFlow, and cloud platforms, with hands-on experience across RAG, semantic search, and LLM-powered workflows. Experienced in scalable AI pipelines and MLOps using AWS, Docker, Kubernetes, MLflow, Airflow, and FastAPI. Specialized in AI automation and agentic AI, including multi-agent systems and orchestration using LangGraph, CrewAI, AutoGen, and MCP servers.

Available to hire

AI Engineer with 4+ years of experience building machine learning, generative AI, and data-driven solutions. Skilled in Python, SQL, PyTorch, TensorFlow, and cloud platforms, with hands-on experience across RAG, semantic search, and LLM-powered workflows.

Experienced in scalable AI pipelines and MLOps using AWS, Docker, Kubernetes, MLflow, Airflow, and FastAPI. Specialized in AI automation and agentic AI, including multi-agent systems and orchestration using LangGraph, CrewAI, AutoGen, and MCP servers.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Intermediate

Intermediate

Intermediate

Beginner

Language

Afar

Advanced

Work Experience

AI Engineer at SoFi

May 1, 2025 - Present

Built credit risk models in Python using XGBoost and scikit-learn to predict loan default probability from borrower and application data, improving risk prediction accuracy by 14%. Prepared model-ready datasets using Pandas and SQL by cleaning missing values, outliers, duplicates, and inconsistent fields, reducing preparation time by 30%. Contributed feature engineering (DTI, credit utilization, delinquency, payment-history signals) improving precision by 10%. Developed a loan document assistant with LangChain and Hugging Face Transformers using RAG to extract/summarize key information, reducing manual review time by 35% across 10K+ documents. Implemented an RAG-based financial Q&A workflow with LlamaIndex and Pinecone to retrieve internal lending policies and explain eligibility and risk factors. Exposed the trained model as a real-time scoring API via FastAPI and deployed with Docker on AWS. Used MLflow for tracking and evaluation; supported consistent, scalable inference in producti

AI Engineer at HCL Tech

April 1, 2022 - December 1, 2023

Contributed to RAG pipelines and knowledge agents on AWS using LangChain, FAISS, and Pinecone for clinician FAQs, reducing document lookup time by 35% and improving care team productivity. Engineered NLP summarization for unstructured EMR notes using PyTorch and Hugging Face Transformers, reducing triage review effort by 20% while maintaining clinical accuracy. Built healthcare data pipelines with Apache Spark and DuckDB to normalize multi-source EHR data, improving feature engineering throughput and reducing model training time by 25%. Integrated MCP Servers to securely connect AI agents with clinical knowledge bases and internal APIs, reducing custom integration effort by 30%. Designed model monitoring dashboards with MLflow and FastAPI to track drift, latency, and evaluation metrics. Established automated retraining pipelines for classification and retrieval models using Jenkins and Docker to support 20+ deployments with reliable rollback and consistent knowledge-agent performance.

ML Engineer at Coforge

February 1, 2021 - March 1, 2022

Supported development of a demand forecasting pipeline for e-commerce pricing optimization using XGBoost, LightGBM, and Prophet on 3+ years of historical sales data, improving forecast accuracy by 12% and reducing inventory holding costs by 8%. Validated price elasticity using Random Forest and Bayesian techniques across price points, incorporating Feast features (popularity, seasonal trends, historical patterns) to support 10+ pricing decisions. Assisted in enhancing a price optimization engine by combining revenue forecasts, profit margin, and competitor pricing signals to generate near real-time recommendations, increasing revenue by 10% and improving gross margin by 6%. Operated Kafka- and SQL-based pipelines processing 5M+ daily transactions and competitor feeds to transform demand and elasticity signals into features for continuous retraining and monitoring. Used MLflow for experiment tracking, model validation, and A/B testing workflows to compare strategies and monitor drift. C