Engineering Journey

Evolution, professional history, and engineering toolkit.

Currently working as a Founding AI Engineer at DocuraHealth (YC W26), Previously, I worked as a Machine Learning Engineer at Pibit.ai (YC W21), and a Founding AI Engineer at Aarogya ID.

During college, I worked across 5 startups as an AI & Software Engineer, worked at Open Source organization, and taught as a Python Instructor at USF.

Below is detailed information of all my work

Founding AI Engineer @ DocuraHealth (YC W26)

2026 - Present San Francisco, United States
  • 0 -> 1
  • Built and improved a Planning Agent system for report generation workflows, orchestrating extraction planning, sample coordination, report preparation, and iterative refinement/replanning for failed or low-confidence outputs, reducing manual operational effort by ~50%.
  • Developed Verification Agent layers across multiple AI pipelines to validate extracted data and generated reports, reducing report inconsistencies and manual review/correction workload by ~40% for operations teams.
  • Worked on Context Handling systems to improve reasoning consistency and structured output reliability, leading to noticeably higher report quality and reduced regeneration cycles.
  • Optimized report generation and Review of Records (ROR) workflows using asynchronous processing and parallel execution strategies, decreasing processing latency by ~60% and significantly improving throughput for large-scale healthcare record handling.
  • Enhanced OCR and document extraction pipelines by improving prompt behavior, extraction orchestration, and validation logic, improving extraction accuracy and reducing downstream correction effort.
  • Integrated and onboarded new healthcare client workflows, ensuring generated outputs matched client-specific templates, formatting standards, and reporting requirements while reducing template adjustment/review effort by ~50%.
  • Worked on Phone Agent workflows capable of processing call/audio inputs and converting extracted information into structured healthcare forms, reducing manual form-filling effort for operational workflows.
  • Reverse engineered a proprietary .ds2 (Olympus CELP-based) audio format and built a custom decoding pipeline (DS2 → WAV → OGG Opus) to enable accurate transcription using Deepgram/Whisper, overcoming lack of native FFmpeg support.
  • Led end-to-end development of AI infrastructure, workflow automation systems, frontend upload/review flows, and production healthcare AI pipelines as the primary engineer.
  • Tech Stack: Claude Opus 4.7, GPT-5.3, Python, FastAPI, Docker, LlamaIndex, Deepgram, Whisper, Next.js, AWS, Async Processing, OCR Pipelines, Multi-Agent Systems, Prompt Engineering, AI Verification Systems, Audio-to-Structured-Data Pipelines, Report Generation Workflows.

Machine Learning Engineer @ Pibit.ai (YC W21) Series A

2025 Bangalore, India
  • Developed a Python-based comparison system using Pandas and Openpyxl to validate model outputs against ground truth data. The system automatically highlighted discrepancies and critical issues, enabling QA and Operations teams to reduce manual review effort by ~70% and generate actionable reports instantly.
  • Improved the performance of the Exmod LLM system by iterating on prompts, evaluating model behavior, and analyzing responses through Langfuse, resulting in a ~25% improvement in document extraction accuracy and reliability.
  • Identified and resolved data contamination and document quality issues across multiple workflows, improving data integrity and downstream extraction performance.
  • Enhanced supplemental document processing pipelines through prompt optimization and backend workflow improvements, reducing manual correction and QA effort by ~40%.
  • Collaborated with cross-functional engineering teams to develop the Piparse package, standardizing document ingestion, preprocessing, and extraction workflows across multiple client pipelines.
  • Contributed to the design and development of an internal prompt management system for centralized prompt versioning, evaluation, and experimentation across large-scale LLM workflows.
  • Tech Stack: GPT 4o, Python, Pandas, Openpyxl, Prompt Engineering, Langfuse, AWS S3, AWS CloudWatch.

Founding AI Engineer @ Aarogya ID

2025 Hyderabad, India
    • 0 -> 1
    • Designed and evaluated a medical question-answering system by benchmarking multiple LLMs including Claude Sonnet 3.5, OpenBioLLM, and Meditron, identifying the most accurate and contextually relevant models for production use.
    • Engineered and optimized document digitization workflows using AWS Textract and Claude 3.5, reducing extraction errors by ~40% across medical documents.
    • Integrated Gemini Flash 2.0 into backend digitization pipelines, improving parsing performance and increasing throughput by ~60% on large PDF files.
    • Led the backend integration of Gemini Flash 2.0, handling complex API responses and workflow orchestration using AWS Lambda, Bedrock, and CloudWatch.
    • Migrated backend storage from AWS RDS to DynamoDB, reducing infrastructure costs while maintaining system performance and scalability.
    • Designed and deployed REST APIs through AWS API Gateway, enabling secure and scalable access to document digitization services.
    • Authored technical documentation covering system architecture, LLM evaluations, API design, workflow automation, and operational handoff processes.
    • Worked closely with founders and product stakeholders to evaluate model performance, improve workflow reliability, and support the evolution of AI-powered healthcare infrastructure.
    • Tech Stack: Claude Sonnet 3.5, OpenBioLLM, Meditron, Gemini Flash 2.0, AWS Lambda, AWS Bedrock, AWS CloudWatch, AWS API Gateway, AWS Textract, DynamoDB, AWS RDS, Python, REST APIs.

Engineering @ Multiple Startups

2022 - 2024 India
  • Worked across 5 startups + 1 open-source organization (part-time/intern): Verbient Technologies, Shoziki Infotech, HomeZing, TCET Open Source, Homestogether, and Universe Simplified.
  • Independently built and deployed CMS platforms and full-stack web applications, managing frontend, backend, deployment, and SEO optimization across multiple startup projects.
  • Led end-to-end feature development and technical execution for client and internal projects, taking ownership from development to deployment in fast-paced startup environments.
  • Developed Statistical ML-powered tools, recommendation systems, and automation-focused solutions to improve personalization, workflow efficiency, and data-driven decision making.
  • Worked on RAG-based chatbot systems and AI-powered product features using LLM workflows to enhance user engagement, contextual search, and information retrieval pipelines.
  • Contributed to backend engineering, API integrations, client-side validation systems, and business logic implementation for scalable web applications.
  • Deployed and managed applications on AWS EC2 environments while handling production-level debugging, updates, and optimization workflows.
  • Collaborated with cross-functional teams, founders, and developers while also taking independent ownership of critical engineering tasks and deliverables.
  • Mentored and taught Python programming at Universe Simplified, helping university students and teaching professionals understand programming fundamentals and practical software development concepts.
  • Demonstrated strong self-learning and leadership abilities by contributing across AI/ML, backend engineering, frontend development, deployment, and technical problem-solving.
  • Tech Stack: Langchain, GPT 4.1, Scikit Learn, NLTK, BeautifulSoup4, Selenium, Python, Flask, Django, React, PHP, Javascript, SQL, Xampp, Git, Github, AWS Ec2 Windows.

Engineering Toolkit

Skills, frameworks, and technical foundations.

Domain Proficiency

Machine Learning AI Agents Multi-Agent Systems RAGs Evaluation MLOps/DevOps Backend Development Full Stack Software Development

Frameworks & Libraries

HuggingFace Langchain LangGraph Pydantic LlamaIndex Crew AI Phidata TensorFlow PyTorch Keras Scikit-learn Numpy Pandas NLTK Spacy Flask FastAPI Giskard DeepEvals

Tools & Platforms

Git Docker LangFuse Langsmith DVC MLflow Postman DataStax Unsloth

Databases

MySQL ChromaDB Pinecone FAISS DynamoDB MongoDB

Cloud & Infrastructure

CI/CD Docker Kubernetes HELM ArgoCD Github Actions AWS EKS AWS Bedrock AWS Lambda AWS S3 Bucket AWS RDS AWS DynamoDB AWS API Gateway AWS CloudWatch AWS EC2

Additional Skills

Next.js PHP React & React Native Teaching
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