Open to opportunities

siddalingappa manasa

@siddalingappamanasa

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Data & AI engineer specializing in RAG, pipelines, and scalable AI-driven solutions.

India

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What I'm looking for

I seek roles building production-grade data and GenAI systems—focused on RAG, ETL pipelines, and scalable model integrations, with opportunities to grow cloud data engineering skills and impact product outcomes.

I am a Data Engineer and AI Engineer focused on building scalable, production-ready data and GenAI systems that drive reliable insights and conversational experiences.

I have designed complete RAG pipelines, ETL-style preprocessing flows, LLM agent frameworks, and document-intelligence chatbots, and I actively analyze LLM behavior, failure modes, and data handling challenges.

My projects include a retrieval-augmented Q&A system with FAISS indexing, an LLM agent task evaluator for hallucination and reasoning analysis, a document-aware conversational system using LangChain, and a CNN-based deepfake detector achieving 90% accuracy.

I work primarily with Python, SQL, Pandas, NumPy, FAISS and related tooling, and I am expanding my cloud data engineering skills on AWS and IBM Cloud while applying strong data-cleaning, transformation, and ETL design practices.

Experience

Work history, roles, and key accomplishments

Data Engineer & AI Engineer

Self Employed

Built end-to-end data and GenAI systems including RAG pipelines, ETL preprocessing flows, LLM agent frameworks, and document-intelligence chatbots to support scalable AI-driven solutions.

Python SQL ETL RAG Faiss Data Cleaning Embeddings

Education

Degrees, certifications, and relevant coursework

IIT Ropar

Minor in Artificial Intelligence, Artificial Intelligence (Minor)

2025 -

Pursuing a Minor in Artificial Intelligence at IIT Ropar beginning in 2025 with coursework focused on AI fundamentals and applied machine learning.

Koneru Lakshmaiah Institute of Science and Technology

Bachelor of Technology, Information Technology

Grade: CGPA: 7.6

Completed a B.Tech in Information Technology with a CGPA of 7.6, covering software development, data engineering, and systems courses.

St. Francis College for Women

Intermediate, Intermediate (Pre-University)

Grade: CGPA: 8.05

Completed intermediate (pre-university) studies with a CGPA of 8.05 focusing on science and mathematics preparation for engineering undergraduate study.