Rahul Jain

Engineering Manager @Bristlecone

New Delhi, DL, IN
MOBILE NUMBERS
+91 *********19

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WORK HISTORY

Oct 2022 — Present

Engineering Manager @Bristlecone

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Noida, IN

Led the team in integrating payment gateways and migrating IoT APIs using REST, MERN stack, Java, and SAP BTP, resulting in enhanced operational efficiency and seamless payment processing.• Developed a supply planning dashboard with Java to streamline supply chain operations.• Obtained certifications in Gen AI and IoT service frameworks, showcasing expertise in emerging technologies.built everything from small, single-function internal applications to large-scale, globally distributed platforms

EDUCATION

1996 — 2009

Navyug Education Society(NES)

Student, School

2010 — 2014

B.M. Institute of Engineering and Technology

Bachelor's degree, Computer Engineering

SKILLS

MysqlCore JavaGitResponsive Web DesignRetails ManagementCascading Style Sheets (Css)JavascriptAjaxHtmlData StructuresCssPhotoshopWebsphereMicrosoft AzureWeb ServicesSqlRestful WebservicesHibernateDb2EclipseMicrosoft Sql ServerNetbeansSpring FrameworkWeb DevelopmentC++Software DevelopmentJavaserver Pages (Jsp)SoapXmlSpringsJ2ee Web ServicesJ2eeBloggingJspCobolGithubJqueryMavenJiraHtml5

ABOUT RAHUL JAIN

A multifaceted technology leader with over a decade of comprehensive experience in application development and platform engineering, with deep specialization in Java full-stack development and cloud-native architectural paradigms. Adept at orchestrating the end-to-end delivery of scalable, high-performance systems, with notable accomplishments including the successful integration of enterprise-grade payment gateways and the implementation of a Java-based dashboard that optimized supply chain operations, yielding a 15% increase in efficiency.Demonstrates a proven track record of fostering high-performing, cross-functional teams and delivering transformative outcomes by aligning digital strategy with technical execution. Possesses extensive expertise in modern software delivery practices—spanning DevOps, microservices architecture, and robust API ecosystems—deployed seamlessly across agile and waterfall environments.In addition to core engineering competencies, brings significant depth in MLOps and AI platform engineering, having architected and operationalized end-to-end pipelines for machine learning models across diverse frameworks such as TensorFlow, PyTorch, Apache Mahout, Hugging Face Transformers, and GPT-based systems. Successfully accelerated AI adoption across organizations, enabling up to 50% user growth through platform scalability and performance optimization—realized via architectural innovations that reduced system latency by 30% and increased throughput by 15–20%.Strategically aligned with enterprise goals, consistently driving innovation and enabling organizations to deliver integrated, intelligent digital experiences at scale.

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