Company: Fidelity International Role: Software Development Engineer (SDE) Team: AI Foundations Employment: Full-time since graduating in 2025 Primary area: AI / Generative AI / AI platform enablement Key work: Bringing and onboarding AI models for organizational use Models/platforms discussed: OpenAI/ChatGPT, Claude, and POCs involving Google models Responsibilities: AI model onboarding/integration, POCs, evaluating AI capabilities, and supporting GenAI initiatives Technical areas: LLMs, tokenization, embeddings, RAG, Agentic RAG, transformers, encoder-decoder architectures, prompt engineering, and chatbot architectures Professional focus: Building AI capabilities that can be adopted and consumed by teams across Fidelity International.

Harshit Jhanwar

Company: Fidelity International Role: Software Development Engineer (SDE) Team: AI Foundations Employment: Full-time since graduating in 2025 Primary area: AI / Generative AI / AI platform enablement Key work: Bringing and onboarding AI models for organizational use Models/platforms discussed: OpenAI/ChatGPT, Claude, and POCs involving Google models Responsibilities: AI model onboarding/integration, POCs, evaluating AI capabilities, and supporting GenAI initiatives Technical areas: LLMs, tokenization, embeddings, RAG, Agentic RAG, transformers, encoder-decoder architectures, prompt engineering, and chatbot architectures Professional focus: Building AI capabilities that can be adopted and consumed by teams across Fidelity International.

Available to hire

Company: Fidelity International
Role: Software Development Engineer (SDE)
Team: AI Foundations
Employment: Full-time since graduating in 2025
Primary area: AI / Generative AI / AI platform enablement
Key work: Bringing and onboarding AI models for organizational use
Models/platforms discussed: OpenAI/ChatGPT, Claude, and POCs involving Google models
Responsibilities: AI model onboarding/integration, POCs, evaluating AI capabilities, and supporting GenAI initiatives
Technical areas: LLMs, tokenization, embeddings, RAG, Agentic RAG, transformers, encoder-decoder architectures, prompt engineering, and chatbot architectures
Professional focus: Building AI capabilities that can be adopted and consumed by teams across Fidelity International.

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Experience Level

Expert
Expert
Expert
Expert
Intermediate
Intermediate
Intermediate

Work Experience

On -Site Graduate Programmer (AI Engineer) at Fidelity International
January 1, 2025 - Present
Designed prompt optimization pipelines using DSPy to train on golden reference answers for optimal prompts in enterprise GenAI workflows. Built an internal GenAI learning platform for teams to explore AI tools, workflows, and accelerators. Developed multiple GenAI accelerators including document-to-Markdown conversion, Excel sheet analyzer, PowerPoint/document analyzers, and audio transcription/analysis pipelines, plus summarization workflows. Prototyped agentic orchestration frameworks using LangChain, AutoGen, OpenAI Agents SDK, and LangSmith for evaluation, with n8n. Implemented LLM evaluation pipelines using RAGAS and DeepEval to benchmark retrieval quality and reduce hallucinations. Researched and benchmarked OCR frameworks (PaddleOCR, olmOCR, Azure Document Intelligence) and implemented a unified OCR abstraction API adopted by ~40% of internal developers for standardized ingestion. Provided structured guidelines for choosing RAG architectures and identified PageIndex RAG as optim
Remote Data Science & Machine Learning Summer Analyst at IBM, Inc.
June 1, 2024 - July 1, 2024
Led development and implementation of data collection and preprocessing pipelines for a multilingual language translation model across 10 languages, improving scalability and reducing data processing time by 30%. Managed a team of 5 college students and mentored them to deliver project milestones within deadlines. Executed algorithmic optimizations that enhanced translation accuracy and system efficiency, supporting overall project success.
Remote Data Scientist Intern at Code Clause
June 1, 2023 - July 1, 2023
Engineered a movie recommendation system using machine learning algorithms, improving recommendation accuracy by 20% on a dataset of 500,000+ user ratings. Streamlined data processing workflows, reducing processing time by 30% through optimized data handling and feature engineering. Presented key insights to stakeholders showing how optimizations improved user satisfaction and recommendation accuracy.

Education

Bachelor’s of Technology in Computer Science and Engineering at University of Petroleum and Energy Studies, School of Computer Science
January 1, 2021 - May 1, 2025
Class XII (CBSE) at A.V.S Public School, Bijoliya, Rajasthan, India
January 1, 2018 - May 1, 2020
Class X (CBSE) at A.V.S Public School, Bijoliya, Rajasthan, India
January 1, 2016 - May 1, 2018

Qualifications

Add your qualifications or awards here.

Industry Experience

Financial Services, Software & Internet

Experience Level

Expert
Expert
Expert
Expert
Intermediate
Intermediate
Intermediate

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