• Having 14+ Years of experience in AI application development, leveraging advanced technologies such as LangChain LangSmith, RAG, Hugging Face, and FastAPI.
• Proficient in integrating LLM models like GPT, T5, llama, and BERT with modern cloud platforms including Google Cloud Platform (GCP) and Microsoft Azure, and seeking an opportunity to drive innovation in AI-powered solutions, utilizing expertise in ML models, NLP, Computer Vision and cloud-native technologies.
• Design and development of GenAI-powered applications using state-of-the-art LLMs, including GPT, BERT, and Hugging face Transformers, integrated with LangChain, LangSmith, RAG, and FastAPI for enhanced performance.
• Designed and implemented Retrieval-Augmented Generation (RAG) workflows, significantly improving the accuracy and relevance of AI-generated content.
• Developed a chatbot for customer support using NLP capabilities to automate responses to frequently asked questions.
• Fine-tuned and scalable machine learning models using Hugging face transformers and datasets, focusing on NLP and computer vision projects.
• Built and managed RESTful APIs with FastAPI and Flask to serve AI models, ensuring seamless integration with front-end applications.
• Orchestrated containerized deployments using Kubernetes and Docker, achieving high availability and scalability in production environments.
• Automated CI/CD pipelines using GitLab and GitHub Actions, reducing deployment time and enhancing the reliability of software releases.
• Analyzed user interaction data to identify trends and improve chatbot performance through iterative testing and refinement.
• Developed and maintained CI/CD pipelines using GitLab CI/CD and GitHub Actions automating the build, test, and deployment processes for multiple microservices.
• Strong automation scripting with Python, YAML, and Bash.
• Implemented and managed Kubernetes clusters to orchestrate Docker containers, improving deployment speed and reliability.
• Data model review, run the code refactoring and optimization, containerization, deployment, versioning, and monitoring of its quality.
• Experienced in version control systems with Gitlab, and GitHub.
• Skilled in monitoring and logging using Grafana, Splunk, Prometheus, Sysdig, Dynatrace, and Datadog.
• Proficient in CI/CD pipeline configurations using GitLab CI/CD and GitHub Actions.
• Implemented AI and ML model pipelines, increasing deployment frequency.

Program Languages: Python, C/C++, Java, Kotlin

Gen AI Frameworks & Tools: LangChain, LangSmith, RAG, Groq, Hugging Face

AI & Machine Learning: TensorFlow, Pytorch, NLP, Computer Vision

CI-CD Platforms: Gitlab, Jenkins, GitHub Actions

Operating Systems: Mac, Windows, Linux

Version Control: Git, Gitlab, GitHub

Cloud Services Platform: GCP, AWS, Azure

Configuration Management: Ansible, Terraform

Containerization and Orchestration: Docker, Kubernetes

Monitoring and Logging: Prometheus, Grafana, , Sysdig

Networking and Security Concepts: TCP/IP, UDP, DNS, SSH, HTTPS

Agile Methodologies: Scrum, Kanban

Database: MySQL, PostgreSQL, MongoDB

Scripting: Python, Bash, PowerShell, YAML

Build Tools: Ant, Maven, Gradle

Collaboration: JIRA, Confluence

Development IDE: VS code, PyCharm, IntelliJ, Eclipse, VIM

Role: Senior AI Engineer

Timeline: July 2023 - Present

• Led AI development projects, leveraging OpenAI API, LangChain, RAG, LangSmith, and FastAPI to build intelligent AI chatbots and context-aware systems.
• We integrated advanced AI models with cloud platforms such as GCP and Azure, ensuring robust and scalable AI deployments.
• We implemented version control and continuous integration strategies using GitLab and GitHub Actions, enhancing development workflows and project management.
• Managed Kubernetes clusters to deploy machine learning models, optimize resource allocation, and maintain system reliability.
• Automated AI/ML model deployment and optimization of GenAI/ML models in production.
• Implementing CI/CD pipelines for continuous integration and deployment ensures that updates and improvements to the chatbot are rolled out smoothly.
• Integrate Dialogflow with Vertex AI and deploy the chatbot application on GKE. This setup allows for automated testing, building, and deployment, ensuring the chatbot remains up-to-date with the latest features and improvements.
• Implemented AI and ML model CICD pipelines for SIT, PreProd, and Prod environments., increasing deployment frequency.
• Integrated CI/CD pipelines using GitLab CI and GitHub Actions.
• Deployed and configured applications using Helm Charts on Kubernetes, streamlining the deployment process.
• Managed cloud infrastructure on GCP, optimizing cost and performance.
• Monitored system performance with Prometheus and Grafana.
• Collaborated with data scientists and engineers to integrate ML models into applications.
• Managed and configured GitHub Artifactory for efficient version control and artifact management, enhancing deployment processes and maintaining repository health.
• Implemented infrastructure monitoring solutions using Prometheus and Grafana, Dynatrace, Datadog, and Sysdig providing real-time visibility into server and container metrics.
• Utilized Docker and Kubernetes For containerization of applications, streamlining the development and deployment process.
• Experience with version control tools like GIT, and Gitlab.

Environment: Python, LangChain, Groq, RAG, NLP, TensorFlow, OpenAI API, Microservices, Docker, Kubernetes,

Jira, Git, GitLab, GitHub action, GCP, Java, Fastlane, Gradle, Node.js, React Native, JavaScript, IOS/XCode, Android

SDK, NDK, C/C++, shell, SQLite, MongoDB, MySQL, PostgreSQL DynamoDB, VS code etc.

Vectone Mobile

Role: Tech Lead- AI Solutions

Timeline: Mar 2021 - May 2023

• Spearheaded AI development projects, leveraging OpenAI API, and LangChain to build an AI chatbot
• Integrated advanced AI models with cloud platforms such as GCP and Azure, ensuring robust and scalable AI deployments.
• Collaborated with cross-functional teams to deliver AI-driven solutions, focusing on end-to-end development from model training to deployment.
• Implemented version control and continuous integration strategies using GitLab and GitHub Actions, enhancing development workflows and project management.
• Managed Kubernetes clusters for deploying machine learning models, optimizing resource allocation, and maintaining system reliability.
• Utilized OpenCV for image processing tasks, enabling the chatbot to handle visual inputs and provide relevant responses.
• Conducted data preprocessing and feature engineering on large datasets to optimize model performance.
• Implementing CI/CD pipelines.
• Developed and maintained Java-based web applications, improving application performance.
• Designed and implemented RESTful APIs, facilitating seamless communication between front-end and back-end systems.
• Managed provisioning profiles, certificates, and app store submissions through Fastlane, ensuring compliance with platform guidelines.
• Deployed ML models using Kubernetes, ensuring scalability and high availability.
• Integrated CI/CD pipelines with AWS and Kubernetes clusters.
• Utilized Docker for containerization of applications, streamlining the development and deployment process.
• Experience in Java, Kotlin, Android, XCode, and IOS development environments.
• Participate in the planning/estimating of each sprint with CI & CD pipeline and processes

Environment: Python, Colab, LangChain, Vertex AI, OpenCV, NLP, TensorFlow, Dialogflow, Microservices,

Docker, Kubernetes, Jira, Jenkins, Git, Github action, AWS, Java, Gradle, Node.js, React Native, JavaScript,

IOS/XCode, Android SDK, NDK, C/C++, shell, SQLite, MongoDB, MySQL, PostgreSQL DynamoDB, VS code etc.

Trimble INC

Role: Lead Software Engineer

Timeline: Mar 2016 - April 2020

• Design and Implemented the copilot mobile app on Android and IOS.
• Experience with version control tools like GIT, and Bitbucket.
• Has been responsible for deploying an app to the Google Play Store and Apple App Store.
• Experience with the Gradle build system and maintaining different flavors.
• Experience with Gradle (android code build) and XCode build (iOS code build).
• Familiarity with the code signing process for iOS and Android.
• Demonstrates ability to have successfully deployed multiple, complex technical projects.
• Experience in Android, IOS, React Native, and Xamarin app deployment.
• Responsible and take full ownership of co-pilot customer issues.
• Responsible for overseeing all activities within a team.
• Responsible for how to approach tasks and develop a plan to accomplish them.
• Responsible for distributing information to team members and stakeholders.
• Participate in high-level design discussion meetings.
• Git code check-in/checkout, attending code review meetings.
• Build and integrate feature branches to Co-pilot core software.
• Error handling, tracing, and debugging Improve the performance and scalability.

Environment: Git, AWS, Python, OpenCV, NLP, TensorFlow, FastAPI, GitHub, GitHub Actions, Docker,

Kubernetes, Jira, AWS, Gitlab, Jenkins, Java, Gradle, React.js/Node.js, React Native, JavaScript, IOS/XCode build,

Android SDK, NDK, C/C++, Python, shell, SQLite, MongoDB, MySQL, PostgreSQL DynamoDB, VS code etc.

Accenture

Role: Software Engineering Team Lead

Timeline: June 2014 - Mar 2016

• Experience with migrating applications from customer on-premises to the cloud (Azure).
• Involved different development teams and multiple simultaneous software releases.
• Proposed branching strategies for using Version Control Systems Git and Created branches, performed merges, pushing code to the central repo.
• Provided support to enterprise applications and monitoring systems including deployment support and troubleshooting for other development teams.
• Experience in creating users, groups, and roles in LDAP/AD servers.
• Participate in the planning/estimating of each sprint with Azure DevOps CI & CD tools and processes
• Experience with version control tools like GIT, and Bitbucket.
• Has been responsible for deploying an app to the Google Play Store.
• Experience with the MS build system and maintaining different flavors.

Environment: Git, Azure Repos, C#/. Net4.5, WPF/MVVM, MS Dynamic CRM2013, TFS2013, Xamarin, Visual

Studio V2013, MS Build tools, Azure DevOps, etc.

ABB

Role: Senior Python Engineer

Timeline: Oct 2011 - May 2014

• Build and integrate the service with robot ware.
• Writing Unit test cases for the service using pytest
• Writing functional test cases using JMeter
• Verify the robot ware service functionalities on RC/VC.
• Error handling, tracing, and debugging.
• Improve the performance and scalability of the product.

Environment: Python, VxWorks6.9, WRLinux4.0, Robotware.6.0, JavaScript, RobotStudio6.0, Visual Studio v2010,

TS Build tools, TFS, SSH, CAN Protocol, Putty, FileZilla, WinSCP, RC/VC, JMeter, Ruby.

NOKIA

Role: Integration Engineer

Timeline: Oct 2008 - Sep 2011

• Understanding the market requirements clearly
• Configuring and integrating software features into products.
• Driving the system-level debugging and tracing to achieve product quality targets.
• Optimize product configuration to fine-tune performance.
• Enabled/Disabled region-specific application by using feature flags
• Mobile Crash debugging.

Environment: Symbian OS/ S60 platforms, Python. C/C++, I-maker, synergy, fast trace, Energy Proflers, Perl,

WLAN, BT, USB, Mobile Crash Analyzer tool, hook logger, etc.