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I am a Senior Generative AI & Machine Learning Engineer with 11+ years of hands-on experience building and deploying production-grade AI systems across finance, healthcare, retail, insurance, and telecommunications. I specialize in LLM-powered applications, Retrieval-Augmented Generation (RAG), model fine-tuning, prompt engineering, and scalable cloud-based ML deployments. I have built enterprise-grade GenAI services using AWS Bedrock, Azure OpenAI, LangChain, and LangGraph, and I’ve designed multi-agent workflows and RAG pipelines for domain-specific knowledge retrieval and document understanding. I enjoy collaborating with data engineers, DevOps, and product teams to deliver compliant, explainable, and observable AI solutions that drive business value in regulated environments. I’m passionate about building robust monitoring, governance, and security into AI systems while continuously improving model quality and reliability.…I am a Senior Generative AI & Machine Learning Engineer with 11+ years of hands-on experience building and deploying production-grade AI systems across finance, healthcare, retail, insurance, and telecommunications. I specialize in LLM-powered applications, Retrieval-Augmented Generation (RAG), model fine-tuning, prompt engineering, and scalable cloud-based ML deployments. I have built enterprise-grade GenAI services using AWS Bedrock, Azure OpenAI, LangChain, and LangGraph, and I’ve designed multi-agent workflows and RAG pipelines for domain-specific knowledge retrieval and document understanding. I enjoy collaborating with data engineers, DevOps, and product teams to deliver compliant, explainable, and observable AI solutions that drive business value in regulated environments. I’m passionate about building robust monitoring, governance, and security into AI systems while continuously improving model quality and reliability.

Achyut Ha P

AI Engineer, Data Scientist, AI Developer

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I am a Senior Generative AI & Machine Learning Engineer with 11+ years of hands-on experience building and deploying production-grade AI systems across finance, healthcare, retail, insurance, and telecommunications. I specialize in LLM-powered applications, Retrieval-Augmented Generation (RAG), model fine-tuning, prompt engineering, and scalable cloud-based ML deployments. I have built enterprise-grade GenAI services using AWS Bedrock, Azure OpenAI, LangChain, and LangGraph, and I’ve designed multi-agent workflows and RAG pipelines for domain-specific knowledge retrieval and document understanding. I enjoy collaborating with data engineers, DevOps, and product teams to deliver compliant, explainable, and observable AI solutions that drive business value in regulated environments. I’m passionate about building robust monitoring, governance, and security into AI systems while continuously improving model quality and reliability.…I am a Senior Generative AI & Machine Learning Engineer with 11+ years of hands-on experience building and deploying production-grade AI systems across finance, healthcare, retail, insurance, and telecommunications. I specialize in LLM-powered applications, Retrieval-Augmented Generation (RAG), model fine-tuning, prompt engineering, and scalable cloud-based ML deployments. I have built enterprise-grade GenAI services using AWS Bedrock, Azure OpenAI, LangChain, and LangGraph, and I’ve designed multi-agent workflows and RAG pipelines for domain-specific knowledge retrieval and document understanding. I enjoy collaborating with data engineers, DevOps, and product teams to deliver compliant, explainable, and observable AI solutions that drive business value in regulated environments. I’m passionate about building robust monitoring, governance, and security into AI systems while continuously improving model quality and reliability.

Available to hire

I am a Senior Generative AI & Machine Learning Engineer with 11+ years of hands-on experience building and deploying production-grade AI systems across finance, healthcare, retail, insurance, and telecommunications. I specialize in LLM-powered applications, Retrieval-Augmented Generation (RAG), model fine-tuning, prompt engineering, and scalable cloud-based ML deployments. I have built enterprise-grade GenAI services using AWS Bedrock, Azure OpenAI, LangChain, and LangGraph, and I’ve designed multi-agent workflows and RAG pipelines for domain-specific knowledge retrieval and document understanding.

I enjoy collaborating with data engineers, DevOps, and product teams to deliver compliant, explainable, and observable AI solutions that drive business value in regulated environments. I’m passionate about building robust monitoring, governance, and security into AI systems while continuously improving model quality and reliability.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

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Expert

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Expert

Intermediate

Language

English

Fluent

Work Experience

GenAI/ML Engineer at Jefferies Financial Group Inc

May 1, 2024 - Present

Led the end-to-end development of enterprise GenAI applications on AWS (SageMaker, EMR, Redshift) and Bedrock, designing multi-agent runtimes with MCP tool-calling and CrewAI orchestration for role-based workflows. Built Retrieval-Augmented Generation pipelines combining BM25 + vector search with FAISS and Pinecone, enabling grounded financial document analysis and knowledge retrieval. Implemented domain-adapted fine-tuning with PEFT (LoRA/QLoRA) to improve summarization and risk entity extraction. Created secure FastAPI services with OAuth2 and RBAC; deployed on EKS for scalable, real-time inference. Built and evaluated LLM agents using LangChain and LangGraph, automated ingestion/validation of SEC filings and research reports, achieving ~33% workflow efficiency gains. Integrated Neo4j knowledge graphs to enhance fraud detection and compliance analytics. Established monitoring with CloudWatch, X-Ray, and Prometheus; introduced responsible AI guardrails (SHAP/LIME). Conducted automated

AI/ML Engineer & Data Scientist at HCA Healthcare Inc.

November 1, 2022 - April 1, 2024

Led production-grade ML models for patient risk prediction using XGBoost, Random Forest, and deep learning on Google Cloud Vertex AI; delivered end-to-end pipelines with Vertex AI, MLflow, and Cloud Build to accelerate model release cycles by ~25%. Engineered scalable data ingestion and analytics with Cloud Dataflow, Cloud Storage, and BigQuery; integrated external social determinants to improve risk stratification. Implemented OCR and document intelligence with Cloud Document AI; developed NLP pipelines (BERT, spaCy, Transformers) for clinical notes; deployed low-latency inference endpoints on Vertex AI. Applied SHAP/LIME explainability to support HIPAA-compliant audits and clinician trust; built model monitoring and drift dashboards with Looker Studio and Cloud Monitoring. Containerized services with Docker and GKE; delivered GenAI-driven clinical documentation workflows using MedLM (Med-PaLM 2) on Google Cloud for ambient note generation.

AI/ML Engineer at Target Corp

January 1, 2019 - October 1, 2022

Developed forecasting, pricing, and demand-planning ML systems for retail datasets; built scalable ML pipelines in Python and PySpark with Azure data services; engineered time-series features via SQL/dbt and Snowflake. Implemented ARIMA, Prophet, LSTM, and deep learning models, achieving ~25% forecast accuracy improvement for high-volume SKUs. Built ensemble models (XGBoost, Random Forest) for pricing and promotions; incorporated external signals (Nielsen, promotional calendars, social sentiment). Operationalized batch and scheduled inference via Azure Functions with CI/CD across 1,800+ locations; established governance via Azure Purview and telemetry via Azure Monitor. Delivered ML-driven forecasting dashboards in Power BI/Tableau; collaborated with merchandising and supply-chain teams to translate forecasts into pricing/inventory decisions; version-controlled pipelines with Git and Azure DevOps.

Machine Learning Engineer at Allstate

September 1, 2015 - December 1, 2018

Developed and deployed fraud detection, risk scoring, and customer analytics models in a regulated insurance setting. Built supervised ML models (Random Forest, Gradient Boosting, Logistic Regression) for churn, fraud, and risk assessment; improved detection accuracy by ~18%. Developed feature pipelines and actuarial pricing models using GLMs; automated ETL with AWS Glue; deployed to production via AWS Lambda/EC2. Implemented model evaluation frameworks and drift monitoring; optimized Redshift queries; built customer segmentation with K-means. Collaborated with actuarial, underwriting, and data engineering teams to ensure regulatory compliance and production-readiness.

Python Developer / Data Analyst at Ooma Inc

February 1, 2013 - August 1, 2015

Developed Python analytics and ETL systems to support telecom operations; built modular data processing pipelines across SQL Server, MySQL, and Oracle. Built churn and call-drop predictive models; implemented data validation and reconciliation scripts; optimized SQL queries for dashboard responsiveness. Developed A/B testing frameworks; performed VoIP and call-quality analytics; delivered executive dashboards in Tableau and Power BI; integrated analytics outputs into production monitoring workflows.