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Ritu Sharma

@ritusharma1

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Senior AI Engineer building secure, scalable Python AI and RAG platforms.

United States

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What I'm looking for

I’m looking for a team where I can build secure, production-grade AI platforms—especially RAG systems and LLM inference—paired with strong engineering practices: observability, evaluation, and governance for healthcare-grade reliability.

I’m a Senior AI Engineer with 10.5 years of experience designing and building scalable backend systems, APIs, and data platforms using Python. I focus on cloud-native microservices and data engineering pipelines that reliably power enterprise and healthcare AI use cases.

At Centene, I lead the development of enterprise and healthcare Generative AI platforms, including a centralized API management platform. I design secure, serverless AWS workflows for AI/ML pipelines—covering automated ingestion/ETL, CI/CD, authentication, and production monitoring for high availability and zero-downtime deployments.

I’ve built end-to-end RAG pipelines with document ingestion, intelligent chunking, embedding generation, and semantic retrieval. I integrate vector search (FAISS / OpenSearch) for low-latency retrieval, deploy LLM inference APIs with FastAPI, and implement retrieval reranking and production optimizations (caching, batching, prompt tuning) to reduce latency and control inference costs.

I also bring deep reliability and governance experience: I’ve established RAG evaluation and regression detection pipelines, and worked on sensitive-data compliance using HIPAA, GDPR, and CCPA. Earlier roles strengthened my data systems foundation—real-time/batch pipelines, observability (Prometheus/Grafana/Cloud Logging), and streaming migrations using Kafka—so my AI solutions are secure, measurable, and dependable in production.

Experience

Work history, roles, and key accomplishments

Current

Senior AI Engineer

Current

Centene

Jun 2023 - Present (3 years)

Led development of enterprise healthcare AI/Generative AI platforms, including secure serverless workflows for AI/ML pipelines and zero-downtime production deployments. Built centralized API management and end-to-end RAG pipelines with vector search (FAISS/OpenSearch) plus scalable FastAPI LLM inference services and OAuth/Okta-secured access.

Python fastAPI LLM RAG AWS Lambda DynamoDB Vector Search OAuth

Senior Data Engineer

Ankura

Apr 2021 - Jun 2023 (2 years 2 months)

Built and operated distributed, real-time and batch data pipelines across GCP and Azure, emphasizing reliability, orchestration, and data observability. Implemented monitoring and alerting with Prometheus/Grafana and improved failure debugging time by 80% using Cloud Logging/Monitoring and structured metrics/logs.

Python SQL GCP Cloud Storage Batch IAM Azure Kubernetes Docker Apache Airflow Prometheus Grafana CI CD

Senior Software Engineer

Corteva

Oct 2019 - Apr 2021 (1 year 6 months)

Developed production-grade healthcare ML/NLP solutions including time-series forecasting, multi-label classification, and transformer-based models (LSTM/CNN/Transformers). Implemented RAG/NLP systems with evaluation and drift monitoring, supporting model deployment and privacy-preserving approaches using federated learning and FHIR/HL7 interoperability.

Python CNN Transformers NLP RAG Time Series Models Multi Label Classification ML Pipelines Model Monitoring Edge AI Federated Learning

Software Developer

Nike

Jun 2017 - Sep 2019 (2 years 3 months)

Delivered GDPR/CCPA-compliant data compliance and user permission services, including a self-delete capability to support user data erasure. Led the NSP1 to NSP3 migration with automated Kafka pipelines and end-to-end streaming workflows with zero downtime, while optimizing Snowflake and Delta Lake schemas for performance.

Python SQL Apache Kafka Data Streaming Airflow Databricks Snowflake Delta Lake Data Pipelines GDPR CCPA Compliance

Software Developer

HealthEdge

Jun 2015 - Feb 2017 (1 year 8 months)

Developed and maintained Python-based backend services (Flask/Django) providing secure RESTful APIs for healthcare data exchange. Implemented basic production monitoring and logging with the ELK stack to improve system visibility for distributed services.