Architected modular, agent-based AI systems with CrewAI; standardized LLM context via MCP; designed robust prompt and tool-call strategies; built scalable ingestion/indexing pipelines on AWS (Lambda, Step Functions, S3); enhanced retrieval with Titan/OpenAI embeddings; fine-tuned open-source LLMs (LoRA/QLoRA) on SageMaker; deployed low-latency secure microservices with FastAPI on EKS/Lambda; instituted production observability (CloudWatch, Prometheus, Grafana, LangSmith, RAGAS) and fintech-grade security; implemented CI/CD with GitHub Actions and Terraform.

Data Scientist at Accenture

June 1, 2020 - December 1, 2022

Contributed as part of enterprise data science initiatives in Hyderabad, focusing on ML/AI workloads and data-driven solutions across business units.

AI/ML Engineer at Cardinal Health, USA

February 1, 2023 - May 1, 2024

Standardized production NLP serving with Hugging Face, spaCy, and AWS SageMaker; containerized ML services with Docker and deployed to Amazon EKS with auto-scaling and zero-downtime deployments; implemented model monitoring, drift detection, and performance tracking with MLflow and CloudWatch, reducing degradation by 50% through proactive retraining; collaborated with product, data, and security teams to ensure governance and compliance.

Data Scientist at Accenture – Hyderabad, India

June 1, 2020 - December 1, 2022

Designed, built, and deployed production-grade ML and deep learning pipelines on AWS SageMaker for classification, recommendation, NLP, and information retrieval workloads; established robust MLOps practices and monitoring to ensure reliability and traceability; enabled scalable model serving for 100K+ monthly inferences; contributed to transformer-based NLP solutions and end-to-end data processing pipelines across regulated environments.