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I am an AI Engineer with 4+ years of experience building and deploying ML systems across finance and enterprise AI. I design and implement end-to-end AI solutions that deliver measurable business impact while operating in cloud-native environments.\n\nI specialize in generative AI, multi-agent workflows, RAG, and ML Ops, collaborating with cross-functional teams to reduce risk, improve investment decision workflows, and drive value in regulated environments. I thrive on solving complex problems with scalable architectures, and I enjoy turning research into production-grade systems using tools like Spark, Kafka, Docker, Kubernetes, and advanced LLM tooling.…I am an AI Engineer with 4+ years of experience building and deploying ML systems across finance and enterprise AI. I design and implement end-to-end AI solutions that deliver measurable business impact while operating in cloud-native environments.\n\nI specialize in generative AI, multi-agent workflows, RAG, and ML Ops, collaborating with cross-functional teams to reduce risk, improve investment decision workflows, and drive value in regulated environments. I thrive on solving complex problems with scalable architectures, and I enjoy turning research into production-grade systems using tools like Spark, Kafka, Docker, Kubernetes, and advanced LLM tooling.

Sushma A

AI Engineer, Data Scientist, Data Analyst, +4

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I am an AI Engineer with 4+ years of experience building and deploying ML systems across finance and enterprise AI. I design and implement end-to-end AI solutions that deliver measurable business impact while operating in cloud-native environments.\n\nI specialize in generative AI, multi-agent workflows, RAG, and ML Ops, collaborating with cross-functional teams to reduce risk, improve investment decision workflows, and drive value in regulated environments. I thrive on solving complex problems with scalable architectures, and I enjoy turning research into production-grade systems using tools like Spark, Kafka, Docker, Kubernetes, and advanced LLM tooling.…I am an AI Engineer with 4+ years of experience building and deploying ML systems across finance and enterprise AI. I design and implement end-to-end AI solutions that deliver measurable business impact while operating in cloud-native environments.\n\nI specialize in generative AI, multi-agent workflows, RAG, and ML Ops, collaborating with cross-functional teams to reduce risk, improve investment decision workflows, and drive value in regulated environments. I thrive on solving complex problems with scalable architectures, and I enjoy turning research into production-grade systems using tools like Spark, Kafka, Docker, Kubernetes, and advanced LLM tooling.

Available to hire

I am an AI Engineer with 4+ years of experience building and deploying ML systems across finance and enterprise AI. I design and implement end-to-end AI solutions that deliver measurable business impact while operating in cloud-native environments.\n\nI specialize in generative AI, multi-agent workflows, RAG, and ML Ops, collaborating with cross-functional teams to reduce risk, improve investment decision workflows, and drive value in regulated environments. I thrive on solving complex problems with scalable architectures, and I enjoy turning research into production-grade systems using tools like Spark, Kafka, Docker, Kubernetes, and advanced LLM tooling.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Intermediate

Intermediate

Language

English

Fluent

Work Experience

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, 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.