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I am an AI/ML engineer with 11+ years of experience delivering production-grade machine learning, Generative AI, RAG, and agentic AI across healthcare, banking, insurance, retail, and enterprise domains. I am hands-on with Python, SQL, PySpark, Databricks, Snowflake, FastAPI, Scikit-learn, XGBoost, LightGBM, TensorFlow, PyTorch, Azure OpenAI, LangChain, LangGraph, MLflow, Kafka, Airflow, Docker, and Kubernetes. I excel at translating business needs into reliable AI products, reusable ML frameworks, governed data pipelines, API-ready outputs, dashboards, and runbooks. I collaborate with product, security, QA, data, and platform teams to design guardrails, grounding, monitoring, and production support that keep AI solutions robust, compliant, and scalable.…I am an AI/ML engineer with 11+ years of experience delivering production-grade machine learning, Generative AI, RAG, and agentic AI across healthcare, banking, insurance, retail, and enterprise domains. I am hands-on with Python, SQL, PySpark, Databricks, Snowflake, FastAPI, Scikit-learn, XGBoost, LightGBM, TensorFlow, PyTorch, Azure OpenAI, LangChain, LangGraph, MLflow, Kafka, Airflow, Docker, and Kubernetes. I excel at translating business needs into reliable AI products, reusable ML frameworks, governed data pipelines, API-ready outputs, dashboards, and runbooks. I collaborate with product, security, QA, data, and platform teams to design guardrails, grounding, monitoring, and production support that keep AI solutions robust, compliant, and scalable.

Kiranreddy Aragonda

AI Engineer, Data Scientist, Full Stack Developer, +2

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I am an AI/ML engineer with 11+ years of experience delivering production-grade machine learning, Generative AI, RAG, and agentic AI across healthcare, banking, insurance, retail, and enterprise domains. I am hands-on with Python, SQL, PySpark, Databricks, Snowflake, FastAPI, Scikit-learn, XGBoost, LightGBM, TensorFlow, PyTorch, Azure OpenAI, LangChain, LangGraph, MLflow, Kafka, Airflow, Docker, and Kubernetes. I excel at translating business needs into reliable AI products, reusable ML frameworks, governed data pipelines, API-ready outputs, dashboards, and runbooks. I collaborate with product, security, QA, data, and platform teams to design guardrails, grounding, monitoring, and production support that keep AI solutions robust, compliant, and scalable.…I am an AI/ML engineer with 11+ years of experience delivering production-grade machine learning, Generative AI, RAG, and agentic AI across healthcare, banking, insurance, retail, and enterprise domains. I am hands-on with Python, SQL, PySpark, Databricks, Snowflake, FastAPI, Scikit-learn, XGBoost, LightGBM, TensorFlow, PyTorch, Azure OpenAI, LangChain, LangGraph, MLflow, Kafka, Airflow, Docker, and Kubernetes. I excel at translating business needs into reliable AI products, reusable ML frameworks, governed data pipelines, API-ready outputs, dashboards, and runbooks. I collaborate with product, security, QA, data, and platform teams to design guardrails, grounding, monitoring, and production support that keep AI solutions robust, compliant, and scalable.

Available to hire

I am an AI/ML engineer with 11+ years of experience delivering production-grade machine learning, Generative AI, RAG, and agentic AI across healthcare, banking, insurance, retail, and enterprise domains. I am hands-on with Python, SQL, PySpark, Databricks, Snowflake, FastAPI, Scikit-learn, XGBoost, LightGBM, TensorFlow, PyTorch, Azure OpenAI, LangChain, LangGraph, MLflow, Kafka, Airflow, Docker, and Kubernetes.

I excel at translating business needs into reliable AI products, reusable ML frameworks, governed data pipelines, API-ready outputs, dashboards, and runbooks. I collaborate with product, security, QA, data, and platform teams to design guardrails, grounding, monitoring, and production support that keep AI solutions robust, compliant, and scalable.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Work Experience

Lead AI/ML Engineer at McKesson

October 1, 2024 - Present

Led end-to-end AI/ML and GenAI workflows for a healthcare workflow intelligence platform, delivering a governed knowledge search, exception review, decision support, workflow automation, and production monitoring solution. Implemented multi-step agent flows with LangGraph, MCP-style connectors, RAG-based retrieval, source grounding, prompt validation, guardrails, and human-in-the-loop review checkpoints. Built reusable full-stack AI patterns for ingestion, feature preparation, model integration, agent routing, API services, deployment, observability, and support documentation. Established enterprise data access controls (OAuth2/JWT/RBAC) and HIPAA/PHI-conscious designs; instrumented monitoring and reliability patterns using CloudWatch, Prometheus, and Grafana.

AI/ML Engineer & Python Engineer at Wells Fargo

January 1, 2022 - September 30, 2024

Delivered banking risk and customer communications AI/ML workflows, connecting behavioral features, model scoring, explainability, and operational dashboards. Standardized pipelines across Python, PySpark, Kafka, Airflow, Snowflake, MLflow, and SQL reconciliation, with API-ready services, UAT evidence, and production recovery playbooks. Implemented explainable outputs for regulated users, curated datasets, and governance documentation to support governed AI releases.

Python Big Data Engineer at New York Life Insurance

June 1, 2019 - December 31, 2021

Built insurance analytics data pipelines across policy, claims, billing, customer, agent, underwriting, and service activity datasets. Delivered model-ready features for lapse analysis, claim trends, renewal behavior, and payment patterns; published scores, search results, and metadata through API services and controlled consumption patterns. Orchestrated daily/monthly workloads with Airflow, created reporting-ready BI datasets, and ensured data quality with reconciliation and validation checks.

Python Data Engineer at Kroger

August 1, 2017 - May 31, 2019

Built retail data workflows across POS, online orders, inventory, product catalog, supplier, store, promotion, and customer event sources for planning teams. Automated ingestion, distributed processing, and validation checks; delivered KPI data outputs and dashboards. Exposed approved KPIs via Flask/FastAPI services and supported UAT, issue resolution, and production handoffs with CI/CD and monitoring.

Data Engineer at Zensar Technologies

June 1, 2015 - May 31, 2017

Created reusable data preparation utilities, metadata-driven ingestion, SQL templates, and validation patterns for enterprise reporting and data quality automation. Built distributed transformations with PySpark/Spark SQL, exposed outputs via REST APIs, and documented data dictionaries, dependencies, and troubleshooting steps to support analytics and early predictive use cases.