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Indla Madhavi - Sr.AI/Ml_Python_Developer

[email protected]

Location: Newark, Delaware, USA

Relocation: Yes

Visa: GC

Resume file: Madhavi_Indla_AI_ML_Python_Developer_1790014297541.docx Please check the file(s) for viruses. Files are checked manually and then made available for download.

MADHAVI INDLA AI/ML WITH PYTHON DEVELOPER [email protected]| 302-525-1642 | PROFESSIONAL SUMMARY AI/ML with Python Developer with 10+ years of experience designing, developing, testing, deploying, and supporting enterprise applications, AI/ML solutions, Generative AI applications, and data-driven platforms across insurance, healthcare, telecommunications, retail, and banking domains. Strong hands-on expertise in Python, Generative AI, LLMs, RAG, AI Agents, NLP, Machine Learning, Deep Learning, Prompt Engineering, Embeddings, Semantic Search, and Vector Search, developing intelligent enterprise solutions including conversational AI, intelligent search, knowledge assistants, and workflow automation. Experienced in developing production-ready GenAI and agentic AI applications using Google Gemini, Vertex AI, OpenAI APIs, LangChain, LlamaIndex, Python, and FastAPI, including AI agents capable of tool/API invocation, enterprise data access, multi-step workflows, and business process automation. Strong experience designing and implementing RAG pipelines using document ingestion, OCR, chunking, metadata extraction, embeddings, vector databases, semantic and hybrid search, retrieval optimization, grounding, context management, and LLM response evaluation. Extensive Python backend, API, and data engineering experience using FastAPI, Django, Flask, REST APIs, microservices, SQL, Pandas, NumPy, ETL/ELT, data pipelines, data modeling, PostgreSQL, MySQL, Oracle, MongoDB, and SQL Server, integrating AI/ML solutions with enterprise applications and backend systems. Strong cloud and production engineering experience across Google Cloud Platform and AWS, including Vertex AI, Gemini, BigQuery, Cloud Storage, Dataflow, Pub/Sub, Cloud Run, Cloud Functions, AWS Lambda, API Gateway, EC2, S3, RDS, DynamoDB, SQS, SNS, and EventBridge, along with Docker, Kubernetes, Git, Jenkins, CI/CD, Terraform, MLflow, OpenTelemetry, Cloud Monitoring, CloudWatch, Prometheus, Grafana, Splunk, ELK, and Datadog. Experienced across the end-to-end AI/ML lifecycle, including data preparation, feature engineering, model development, evaluation, integration, deployment, monitoring, testing, security, and production support, with strong knowledge of responsible AI, IAM, authentication, authorization, PII protection, data governance, prompt-injection mitigation, PyTest, unit testing, integration testing, API testing, Agile/Scrum, and SDLC, collaborating effectively with data scientists, ML engineers, developers, architects, QA, DevOps, and business stakeholders. TECHNICAL SKILLS Programming: Python, SQL, JavaScript, TypeScript, HTML5, CSS3 AI / Machine Learning: Generative AI, LLMs, AI/ML, NLP, RAG, Prompt Engineering, Embeddings, Semantic Search, Vector Search, Machine Learning, Deep Learning, TensorFlow, PyTorch, Scikit-learn GenAI / LLM: Google Gemini, Vertex AI, OpenAI APIs, LangChain, LlamaIndex, RAG Pipelines, Vector Databases, LLM Integration Python Frameworks: Django, Flask, FastAPI, REST APIs, Microservices Frontend: React.js, JavaScript, TypeScript, HTML5, CSS3, Bootstrap, AJAX GCP: Google Cloud Platform, Vertex AI, Gemini, BigQuery, Cloud Storage, Dataflow, Pub/Sub, Cloud Run, Cloud Functions, Cloud Build, IAM, Cloud Logging, Cloud Monitoring AWS: AWS, Amazon S3, Amazon CloudWatch Data Engineering: ETL/ELT, Data Pipelines, Pandas, NumPy, Data Processing, Data Modeling, Feature Engineering Databases: PostgreSQL, MySQL, Oracle, MongoDB, SQL Server DevOps: Docker, Kubernetes, Jenkins, Git, GitHub, CI/CD, Cloud Build, Linux/Unix Testing: PyTest, Unit Testing, Integration Testing, API Testing Security & Monitoring: IAM, Access Control, API Security, Authentication, Authorization, Input Validation, Cloud Logging, Cloud Monitoring, CloudWatch, Prometheus, Grafana, Splunk, ELK Stack, Datadog, OpenTelemetry Tools & Methodologies : JIRA, Agile, Scrum, SDLC, Code Review, Production Support, CI/CD PROFESSIONAL EXPERIENCE Johnson & Johnson New Brunswick, NJ | April 2025 Present Senior Gemini AI/ML Engineer Designed, developed, and deployed enterprise-grade Generative AI and AI/ML solutions using Google Gemini, Vertex AI, Python, LangChain, and LLM technologies to support intelligent business applications. Built and optimized Gemini-powered conversational AI and AI agent solutions for employee and customer-facing use cases, enabling intelligent question answering, automation, and self-service capabilities. Developed Retrieval-Augmented Generation (RAG) pipelines integrating enterprise documents, knowledge bases, vector databases, embeddings, and semantic search to deliver context-aware and grounded responses. Implemented prompt engineering, prompt templates, structured outputs, function calling, tool use, and agent orchestration for reliable and scalable Gemini-based applications. Developed AI agents capable of reasoning over enterprise data, invoking APIs and tools, executing multi-step workflows, and automating business processes. Integrated Gemini and Vertex AI services with REST APIs, microservices, databases, enterprise applications, and cloud services to build end-to-end AI solutions. Developed Python-based AI/ML services and APIs using FastAPI, implementing reusable components for model inference, document processing, retrieval, and agent workflows. Implemented document ingestion and preprocessing pipelines using OCR, chunking, metadata extraction, embeddings, vector search, and semantic retrieval. Evaluated LLM responses using quality, relevance, grounding, latency, and accuracy metrics and improved solutions through prompt optimization, retrieval tuning, and model configuration. Built scalable AI applications using Google Cloud services, containerization, CI/CD, monitoring, logging, and secure enterprise deployment practices. Implemented responsible AI practices including security, access control, data protection, prompt-injection mitigation, PII protection, and response validation. Collaborated with data scientists, ML engineers, software developers, architects, and business stakeholders to translate requirements into production-ready Generative AI solutions. Designed automated testing and validation frameworks for AI agents, RAG pipelines, APIs, and LLM-powered applications to ensure reliability and production readiness. Environment: Google Gemini, Gemini API, Google Vertex AI, Vertex AI Agent Builder, Generative AI, LLMs, AI Agents, RAG, Prompt Engineering, Agentic AI, Python, FastAPI, LangChain, LlamaIndex, REST APIs, Microservices, Embeddings, Vector Databases, Semantic Search, OCR, NLP, Machine Learning, Deep Learning, Google Cloud Platform (GCP), BigQuery, Cloud Storage, Cloud Run, Docker, Kubernetes, Git, CI/CD, Terraform, MLflow, OpenTelemetry, Pytest, JSON, SQL, Agile/Scrum. Breezeline Miramar, Florida | February 2023 March 2025 Senior AI/ML Engineer Designed, developed, and deployed production-ready AI/ML and Generative AI solutions using Python, machine learning, deep learning, NLP, LLMs, and cloud technologies. Built LLM-powered conversational AI, intelligent search, and virtual assistant solutions to improve customer and employee self-service capabilities. Developed Retrieval-Augmented Generation (RAG) pipelines using embeddings, vector databases, semantic search, document processing, and enterprise knowledge sources. Implemented prompt engineering, prompt templates, response evaluation, grounding, context management, and LLM optimization for reliable AI applications. Developed AI agents and intelligent automation workflows capable of using enterprise tools, APIs, and backend services to execute multi-step business processes. Built Python-based AI/ML services and REST APIs using FastAPI, integrating models with enterprise applications and microservices. Developed data preprocessing and feature engineering pipelines for structured and unstructured data, supporting machine learning and NLP use cases. Integrated LLM and AI services with REST APIs, databases, cloud platforms, and enterprise backend systems to deliver end-to-end AI solutions. Implemented vector search and knowledge retrieval using embeddings, metadata filtering, semantic similarity, and hybrid search techniques. Containerized AI/ML applications using Docker and supported deployment through Kubernetes and CI/CD pipelines. Implemented model and application monitoring, logging, observability, and performance tracking using OpenTelemetry and cloud-native monitoring tools. Applied responsible AI and security practices, including PII protection, access controls, secure API integration, prompt-injection mitigation, and data governance. Developed automated unit, integration, and API tests using Pytest to improve reliability and maintainability of AI/ML applications. Collaborated with data scientists, software engineers, DevOps teams, architects, and business stakeholders to deliver scalable AI solutions aligned with business requirements. Environment: Python, AI/ML, Generative AI, LLMs, NLP, Machine Learning, Deep Learning, RAG, AI Agents, Prompt Engineering, LangChain, LlamaIndex, FastAPI, REST APIs, Microservices, Embeddings, Vector Databases, Semantic Search, OpenAI, Azure OpenAI, Google Gemini, AWS, Azure, GCP, BigQuery, Docker, Kubernetes, Hashi Corp Vault, OpenTelemetry, Git, CI/CD, Terraform, MLflow, Pytest, SQL, NoSQL, Agile/Scrum. AXA Insurance New York | April 2020 January 2023 Senior AWS Python Developer with AI Designed, developed, tested, and deployed scalable Python-based applications, REST APIs, and AI/ML solutions supporting insurance business processes and customer-facing applications. Developed backend services and microservices using Python, FastAPI, Flask, and Django, integrating enterprise applications, databases, and AWS cloud services. Built AI/ML solutions for document processing, NLP, text classification, predictive analytics, and intelligent automation, improving insurance workflow efficiency. Developed robust ETL and data processing pipelines using Python, Pandas, and NumPy to ingest, transform, validate, and analyze structured and unstructured insurance data. Integrated machine learning and NLP models into production applications to automate classification, information extraction, recommendations, and decision-support workflows. Developed event-driven and serverless applications using AWS Lambda, API Gateway, SQS, SNS, and EventBridge to support scalable and asynchronous business processes. Designed and implemented cloud-native solutions using Amazon EC2, S3, RDS, DynamoDB, CloudWatch, and IAM, following AWS security, scalability, and reliability best practices. Developed and integrated secure RESTful APIs with internal and external enterprise systems using authentication, authorization, encryption, validation, and error-handling mechanisms. Built reusable Python modules, libraries, services, and automation scripts following object-oriented programming, clean code, design patterns, and software engineering best practices. Designed and optimized database solutions using PostgreSQL, MySQL, DynamoDB, and SQL, including data modeling, query optimization, indexing, and transaction management. Implemented comprehensive unit, integration, and API testing using Pytest and unittest to improve application quality and production reliability. Containerized Python applications using Docker and supported automated build, testing, and deployment processes through CI/CD pipelines using Git and Jenkins. Implemented application logging, monitoring, error handling, and observability using AWS CloudWatch and OpenTelemetry to identify issues and improve system performance. Collaborated with data scientists, AI/ML engineers, software engineers, architects, QA, DevOps teams, and business stakeholders to deliver scalable and production-ready AI-enabled applications. Environment: Python, AI/ML, NLP, Machine Learning, Deep Learning, FastAPI, Flask, Django, REST APIs, Microservices, AWS, AWS Lambda, API Gateway, EC2, S3, RDS, DynamoDB, SQS, SNS, EventBridge, CloudWatch, IAM, PostgreSQL, MySQL, SQL, Pandas, NumPy, Scikit-learn, Docker, Kubernetes, Git, Jenkins, CI/CD, Pytest, unittest, OpenTelemetry, Agile/Scrum. Costco Issaquah, WA | September 2018 March 2020 Senior Python Full Stack Developer Developed scalable enterprise applications using Python, Django, Flask, and REST APIs. Designed and implemented Python-based microservices to support enterprise application functionality. Developed responsive frontend applications using React.js, JavaScript, HTML5, CSS3, and Bootstrap. Integrated data-driven and AI/ML capabilities into enterprise applications where applicable to support automation and business processes. Developed Python-based data processing and automation workflows using Pandas, NumPy, and SQL. Performed data preprocessing, transformation, validation, and analysis for application and analytical workloads. Developed and optimized SQL queries, stored procedures, and database integrations. Worked with PostgreSQL, MySQL, and MongoDB for application and data requirements. Implemented secure API integrations including authentication, authorization, input validation, and service-level security. Exposed application functionality through scalable RESTful APIs and Python microservices. Developed unit and integration tests using PyTest and Python testing frameworks and participated in debugging and defect resolution. Supported Docker, Jenkins, Git, AWS, Linux, code reviews, production troubleshooting, and Agile/Scrum ceremonies. Environment: Python, Django, Flask, FastAPI, REST APIs, Microservices, React.js, JavaScript, HTML5, CSS3, Bootstrap, AI/ML, NLP, Pandas, NumPy, SQL, PostgreSQL, MySQL, MongoDB, PyTest, Git, Jenkins, Docker, AWS, Linux, JIRA, Agile, Scrum ICICI Bank India | September 2012 October 2015 Python Full Stack Developer Designed, developed, and maintained enterprise applications using Python, Django, and Flask for banking-related business workflows. Developed RESTful APIs and backend services supporting internal applications and business processes. Developed reusable Python scripts and automation utilities for data processing, reporting, application integration, and operational tasks. Implemented backend business logic, application workflows, data validation, exception handling, and error-management functionality. Developed reusable Python modules, libraries, and service components following established development standards. Worked with SQL databases for data extraction, transformation, validation, reporting, and application data management. Designed and optimized SQL queries, stored procedures, and database operations using PostgreSQL and Oracle. Integrated backend services with internal and third-party systems using REST APIs, JSON, and XML. Developed web application components using JavaScript, HTML, and CSS, integrating frontend functionality with Python backend services. Implemented application-level authentication, input validation, exception handling, and secure API integrations. Performed unit testing, debugging, troubleshooting, defect resolution, code reviews, deployments, and production support. Participated throughout the SDLC, including requirements analysis, technical design, development, testing, deployment, production support, and Agile/Scrum ceremonies. Environment: Python, Django, Flask, REST APIs, SQL, PostgreSQL, Oracle, JavaScript, HTML5, CSS3, JSON, XML, Git, Jenkins, Linux/Unix, JIRA, Agile, Scrum CERTIFICATION AWS Certified Administrator Keywords: continuous integration continuous deployment quality analyst artificial intelligence machine learning javascript sthree New Jersey Washington Keywords: continuous integration continuous deployment quality analyst artificial intelligence machine learning javascript sthree New Jersey Washington