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I am an AI/ML engineer with 4+ years shipping production LLM pipelines, multi-agent systems, and agentic AI platforms across legal tech, fintech, and enterprise AI. I thrive on turning ambitious AI ideas into scalable, reliable systems, from patent research platforms on AWS Step Functions to RAG-enabled retrieval and real-time compliance monitoring across portfolio optimization workflows. I enjoy building end-to-end AI solutions that blend research and production, collaborating across teams to deliver robust, auditable, and efficient AI-powered products. My focus is on delivering value to users while maintaining governance, security, and performance at scale.…I am an AI/ML engineer with 4+ years shipping production LLM pipelines, multi-agent systems, and agentic AI platforms across legal tech, fintech, and enterprise AI. I thrive on turning ambitious AI ideas into scalable, reliable systems, from patent research platforms on AWS Step Functions to RAG-enabled retrieval and real-time compliance monitoring across portfolio optimization workflows. I enjoy building end-to-end AI solutions that blend research and production, collaborating across teams to deliver robust, auditable, and efficient AI-powered products. My focus is on delivering value to users while maintaining governance, security, and performance at scale.

Sushma

AI Engineer, Data Scientist, Data Analyst, +5

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I am an AI/ML engineer with 4+ years shipping production LLM pipelines, multi-agent systems, and agentic AI platforms across legal tech, fintech, and enterprise AI. I thrive on turning ambitious AI ideas into scalable, reliable systems, from patent research platforms on AWS Step Functions to RAG-enabled retrieval and real-time compliance monitoring across portfolio optimization workflows. I enjoy building end-to-end AI solutions that blend research and production, collaborating across teams to deliver robust, auditable, and efficient AI-powered products. My focus is on delivering value to users while maintaining governance, security, and performance at scale.…I am an AI/ML engineer with 4+ years shipping production LLM pipelines, multi-agent systems, and agentic AI platforms across legal tech, fintech, and enterprise AI. I thrive on turning ambitious AI ideas into scalable, reliable systems, from patent research platforms on AWS Step Functions to RAG-enabled retrieval and real-time compliance monitoring across portfolio optimization workflows. I enjoy building end-to-end AI solutions that blend research and production, collaborating across teams to deliver robust, auditable, and efficient AI-powered products. My focus is on delivering value to users while maintaining governance, security, and performance at scale.

Available to hire

I am an AI/ML engineer with 4+ years shipping production LLM pipelines, multi-agent systems, and agentic AI platforms across legal tech, fintech, and enterprise AI. I thrive on turning ambitious AI ideas into scalable, reliable systems, from patent research platforms on AWS Step Functions to RAG-enabled retrieval and real-time compliance monitoring across portfolio optimization workflows.

I enjoy building end-to-end AI solutions that blend research and production, collaborating across teams to deliver robust, auditable, and efficient AI-powered products. My focus is on delivering value to users while maintaining governance, security, and performance at scale.

Skills

Experience Level

Expert

Expert

Expert

Expert

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Expert

Expert

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Expert

Expert

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Intermediate

Intermediate

Language

English

Fluent

Work Experience

AI/ML Engineer at New Math Data, LLC

January 1, 2026 - Present

Built agentic AI patent-ability and data pipelines, integrating real-time portfolio insights, risk assessment, and compliance monitoring for 500+ investment professionals. Engineered multi-agent orchestration with LangGraph and MCP using LLaMA-3/4 for research, compliance, and reporting. Delivered an end-to-end data stack and governance framework with prompt-engineering, RAG retrieval, and semantic reasoning across 13 schema collection types, enabling scalable, auditable AI-driven narratives.

Agentic AI Narrative Designer at AgentCore Runtime / Arcweave

January 1, 2026 - Present

Architected and shipped an autonomous narrative-generation platform on AWS Agent Core Runtime and Amazon Bedrock, including a 7-step inference pipeline and automated content generation with zero manual editing. Led end-to-end design of Arcweave-compatible JSON schemas and fidelity controls for multi-scheme data collection, enabling consistent multi-board generation and keeping context through prompting. Implemented dedicated asset generation workflows (images, video, scene art) and automated validation to ensure high-quality outputs with reduced human intervention. Established a human-in-the-loop workflow feeding validated prompts back into the system for targeted story graph corrections, significantly reducing manual content creation effort.

Agentic AI/Data Engineer at New Math Data, LLC

January 1, 2026 - Present

Agentic AI/Data Engineer at New Math Data, building an AI-enabled platform for patentability research and multi-agent orchestration on AWS Step Functions, enabling scalable, automated IP research with low hallucinations and end-to-end governance.

AI/ML Engineer at FIDELITY INVESTMENTS

August 1, 2024 - November 5, 2025

Built GenAI pipeline automating Chief Investment Office workflows, integrating portfolio optimization, real-time market intelligence, and compliance monitoring, serving 500+ investment professionals. Implemented multi-agent orchestration with LangGraph and MCP using LLaMA 3 8B for research, compliance, and reporting; applied semantic routing and task-specific prompts to cut manual memo creation time by 50%. Optimized FinGPT/Palmyra with QLoRA and PEFT for financial summarization and document classification, reducing GPU memory usage by 60%. Established a RAG pipeline leveraging FAISS and Redis for indexing earnings reports and regulatory filings, with production indexing on Azure Vector DB using HNSW + hybrid BM25/semantic reranking, achieving 35% improvements in retrieval relevance.

AI/ML Engineer at Capgemini

June 1, 2023 - June 1, 2023

Delivered a fraud detection system using PyTorch and deep neural networks, reducing false positives by 31% and improving anomaly detection in high-volume transactional environments. Calibrated classification models to address severe class imbalance via SMOTE, boosting recall across multiple financial institutions. Built NLP pipelines with Hugging Face Transformers (BERT) and custom tokenization to extract risk entities, intent signals, and customer sentiment from KYC documents; enabled real-time predictions via FastAPI with Lambda, achieving sub-200 ms latency. Orchestrated end-to-end workflows with Airflow and Spark windowed aggregations; supported model retraining and drift monitoring with MLflow.

AI/ML Engineer at Capgemini

May 1, 2021 - June 1, 2023

Delivered an autonomous research platform for LLM-based patent analysis; built multi-modal, multi-step RAG pipelines with AWS Bedrock and OpenSearch; implemented a 5-phase LLM reasoning pipeline with prompt chaining and semantic ranking, achieving significant reduction in manual IP research effort.

AI/ML Engineer at Capgemini

May 1, 2020 - June 1, 2023

Delivered fraud detection systems using PyTorch and deep neural networks, reducing false positives by 31% and improving anomaly detection in high-volume environments. Addressed class imbalance with SMOTE and KPI integration to boost recall across financial institutions. Built NLP pipelines with Hugging Face Transformers (BERT) and custom tokenization to extract risk entities and sentiment from KYC documents, reducing monitoring time by 30%. Containerized inference with Docker and SageMaker; enabled A/B testing and canary rollouts with sub-200 ms latency, and integrated real-time predictions via FastAPI, Kafka, and Spark windowing with Airflow orchestration.