Anmol Jain
Pune
Summary
Dynamic AI Engineer with experience building scalable, production-grade AI systems across healthcare, insurance, and B2B SaaS domains. Skilled in Python, LLMs, and distributed architectures, with a strong focus on RAG pipelines, multi-agent systems, and document intelligence. Proven track record of deploying end-to-end AI solutions at scale, processing millions of documents and supporting thousands of users. Passionate about designing high-impact AI products that combine deep technical innovation with real-world business outcomes.
Overview
4
4
years of professional experience
2023
2023
years of post-secondary education
Work History
AI ENGINEER
Telomere
Columbia
08.2025 - Current
- Built an agentic AI platform to process large-scale surrogacy documents (up to 2GB per case) and generate structured, citation-backed clinical summaries
- Designed multi-stage pipelines for document ingestion, parsing, embedding, retrieval, and summarization across fragmented medical records
- Implemented agentic workflows to extract pregnancy timelines, family medical history, prenatal and delivery summaries, and vaccination records
- Generated high-impact, structured 4-page clinical summaries, significantly reducing manual chart review effort
- Engineered robust parsing pipelines for unstructured medical data (PDFs, scans, reports) with high accuracy
- Developed a contract-aware RAG-based system to validate surrogate expense requests against complex legal agreements
- Designed multi-agent decision pipelines combining retrieval, contract understanding, and reasoning for real-time validation
- Built logic to evaluate expense eligibility based on financial limits, timelines, and contractual conditions
- Automated DR request workflows, enabling real-time expenditure validation and reducing manual intervention
- Leveraged LLM-based retrieval pipelines to interpret legal documents dynamically and enforce compliance
- Deployed and managed scalable infrastructure using AWS CDK and CloudFormation
- Configured load balancers and implemented horizontal scaling to handle high-throughput workloads
- Built monitoring and alerting systems to track performance, latency, and cost spikes in production environments
AI Engineer
Accacia
Bangalore
01.2025 - Current
- Designed and deployed an AI-driven outreach automation platform for hyper-personalized B2B messaging:
- - Built full-stack architecture using FastAPI, Supabase ,PostgreSQL, with scalable cloud-native deployment
- - Implemented multi-agent pipelines for lead research, tone control, and qualification logic, enabling modular personalization at scale, onboarding 10k+ users while tracking adoption with PostHog
- - Applied entity extraction + semantic scoring to dynamically tailor messages to company, industry, and persona context
- Engineered an AI-powered Chrome extension for sales workflows:
- - Automated LinkedIn and Gmail outreach
- - Enabled real-time, context-aware message generation powered by OpenAI + Perplexity, improving outreach efficiency and conversion
- Built an AI-powered pitch deck generation system, combining graph databases with generative AI:
- - Modeled company, industry, and persona relationships in Neo4j, enabling GraphRAG-style enrichment
- - Queried the graph to assemble structured context, then orchestrated AI pipelines to generate tailored PowerPoint sales decks automatically
- Delivered production-ready AI pipelines with polling, chunking, and fallback logic, ensuring reliability, fault tolerance, and scalability in customer-facing applications
- Shaped AI application architecture by integrating modern stacks (vector search, multi-agent workflows, CRM APIs) with real-world customer needs, setting benchmarks for scalability and measurable business impact
Software Engineer
Turtlemint
Pune
08.2022 - 10.2024
- Architected and deployed an advanced document understanding system:
- - Fine-tuned LayoutLM transformer, achieving 95% F1-score on 103 entity classes
- - Engineered robust data preprocessing with attention mechanisms and spatial embeddings
- - Processed 5000+ diverse document formats with spatial-aware token classification
- Developed state-of-the-art extraction pipeline with CLAUDE Haiku LLM:
- - Built a sophisticated prompting system for 98% extraction accuracy across 40+ insurers
- - Engineered a configurable framework for Prompts, Extraction Keys, and Key Types
- - Optimized token usage through intelligent document chunking
- - Successfully processed 10M+ policy documents
- Innovated a custom in-house PDF parser using pymupdf and pdfminer:
- - Implemented advanced preprocessing and token optimization techniques
- - Achieved 99% accuracy across motor, life, and health insurance documents
- - Unified data from 40+ insurers into structured formats
- Led end-to-end MLOps implementation and deployment:
- - Deployed models using TorchServe with AWS SageMaker integration
- - Built a scalable high-throughput architecture with RabbitMQ and Kafka
- - Handled 10K+ requests per hour with automated retraining and performance monitoring
- Engineered a comprehensive preprocessing pipeline:
- - Used SVM-based text classification for intelligent page ranking
- - Integrated AWS Textract OCR for optimized extraction
- - Reduced processing time from 11 minutes to 11 seconds on 80-page docs
- - Processed over 1 million documents with 99% accuracy
Tech Intern
Turtlemint
Pune
02.2022 - 08.2022
- Developed comprehensive dashboards for various business verticals using Apache Superset and Metabase, showcasing data accuracies and insights, powered by complex queries in MySQL and PostgreSQL.
- Designed and implemented APIs for calculating data accuracies using OCR confidence levels and string matching with ground truth data, enhancing data quality and reliability
Education
BTech - Computer Science
Vishwakarma Institute of Technology
Pune, IndiaSkills
Skills
Languages & Frameworks:
Python, Nodejs, TypeScript, Django, FastAPI, React
AI / ML:
LLMs, RAG, Multi-Agent Systems, NLP, OCR, BERT, Word2Vec, XGBoost, Random Forest, Logistic Regression, LSTM, RNN
AI Engineering & Data Systems:
Prompt Engineering, Document Intelligence, GraphRAG, Graph Databases, LangChain
Cloud & Infrastructure:
AWS (EC2, Lightsail), AWS CDK, CloudFormation, Docker, Kubernetes, Load Balancing, Distributed Systems
Data & Backend Systems:
PostgreSQL, MySQL, MongoDB, Neo4j, Apache Kafka, RabbitMQ, Celery
Analytics & Monitoring:
Supabase, Supabase Edge Functions, Sentry, Kibana, Apache Superset, Metabase
Languages
English
Advanced
C1
Timeline
AI ENGINEER
Telomere
08.2025 - Current
AI Engineer
Accacia
01.2025 - Current
Software Engineer
Turtlemint
08.2022 - 10.2024
Tech Intern
Turtlemint
02.2022 - 08.2022
BTech - Computer Science
Vishwakarma Institute of Technology