Machine Learning Solutions Architect
Resume:
Ahmad,
Mohammad Owais
***********@*****.***
Sr. FullStack
Technical-Solution
ARCHITECT
EDUCATION:
MCA (Master of Computer Application) in 2006 from IGNOU New Delhi.
M.Sc. (Physics, Radio Physics and Electronics) in 1995 from BRABU, Muzaffarpur.
B.Sc. (Physics, Hons) in 1993 from BRABU, Muzaffarpur.
CERTIFICATION:
AWS Certified Solutions Architect – Associate
CBE: Certified Blockchain Expert - Blockchain Council.
WBN: Cisco Security White Belt Ninja - Cisco USA.
Python Advanced Django.
Python Data Science & Machine Learning.
JTRACK [Advance Diploma in JAVA] from Software Technology Group (STG) New Delhi.
PROFESSIONAL SUMMARY
Accomplished Full Stack Architect & Engineering Leader with nearly 17 years of experience in development and driving large-scale, high impact projects across diverse technology stacks, including cloud-based solutions, API development, and microservices architecture. A charismatic leader with a proactive, detail-oriented approach to managing complex projects, combining technical proficiency with a passion for innovation and excellence. Extensive Domain expertise in Banking, Finance, Cisco, CX, Innovation, AI/ML-DL, API, Middleware, E-commerce, CMS/ECM, User Experience, Security, and Cloud Computing. Known for exceptional communication skills and a collaborative mindset, driving impactful results in diverse industry settings.
CORE COMPETENCIES:
TECHNICAL SKILLS
Tech & Tools
:
Java8/11/17, JSP, Servlet, J2EE, Python, TensorFlow, PyTorch, Scikit-learn, Fast API, NumPy, Flask, Django, PySpark, GraphDB, SHAP, Spark MLlib, ML&DL, Boto3, Microservices, Lang fuse, Architecture, Micro Services (REST, SOAP Spark), Spring AI, Spring Boot, Vert.x, Spring WebFlux, Scala, and Akka, Scala/Apache Spark, Apache Kafka, Active MQ, LDAP, AD, Hibernate, JPA, Redis, Couchbase, Junit, Mockito, Raven, JProfiler, Camunda Workflow BPMN, WEM, AEM, Astoria JASON, XML, OpenXML, XSD, Open API, Glue, Open AI.
Front-End
:
Ajax, NodeJS, Express, AngularJS, VueJS, ReactJS, jQuery JavaScript, Bootstrap
DB & Data Engineering
:
Oracle, MySQL, PostgreSQL, NoSQL, MongoDB, DynamoDB, CASANDRA, DB2, Teradata, Snowflake, Domo, ElasticSearch, Databricks (ETL Pipelines - GLU), Data Modeling, Data Quality.
Cloud & DevOps
(GCP, GAP, GKS, Azure, AWS)
:
EC2, EKS, ECS, BigQuery, Amplify, AppSync, GraphQL, CDK, VPC, Kinesis, EventBridge, Cognito, Event Bridge, STS, EFS, Elastic Beanstalk, Lambda, Serverless Compute - AWS Fargate Elastic Cache, S3, ELB, Auto scaling, KMS, CloudFront, CloudFormation, RDS, IAM, SNS, SQS, Redshift, EMR, Route 53, CloudWatch, CloudTrail, WAF, DataDog.
CM Tools
:
Ansible, Caph, Puppet, Terraform, CloudFormation, JSON.
DevOps, Build and CICD Tools
:
GitHub, GitLab, GitHub Action, AWS CodePipeline. Maven, Jenkins, Groovy, Shell Script, Helm Chart, Artifactory, Ansible, Dockers, K8s, OpenShift, OpenStack, DataBricks.
Security,Compliance and Data Protection
IAM policies, OAuth2. 0, SSO, SAML, AWS Cognito, GDPR, HIPAA, PCI DSS, FDA, TLS/SSL, KMS, AWS Xray, Raven Scanner and SonarQube, WAFs etc.
Reporting Tools
Jira, Rally, Confluence.
Observability Tools
Dynatrace, Grafana, Splunk, CloudWatch, CloudTrail, ELK Stack, Datadog
Methodologies and Operation
Agile/Scrum, ServiceNow, SR, CR, Incident Management, SLA, SLO, SLI
FUNCTIONAL & TECHNICAL SUMMARY
Having hands-on experience with infrastructure as code (IaC) tools like Terraform, CloudFormation, and Ansible, and I’ve integrated CI/CD pipelines using platforms like Jenkins, GitHub Actions, and GitLab CI. I’m also skilled in containerization and orchestration with Docker and Kubernetes, ensuring systems are highly available and fault tolerant.
Over the years, I’ve architected and deployed enterprise-grade solutions across AWS, Azure, and Google Cloud, always focusing on cost-efficiency, scalability, and security. I’ve also used tools like SonarQube and OWASP ZAP for static and dynamic code analysis to maintain high code quality and security standards.
Specialize in designing and implementing system architectures using tools like Draw.io, Lucid chart, Microsoft Visio, and ArchiMate to create clear and scalable workflows and diagrams. My experience includes building microservices architectures, event-driven systems, and cloud-native applications that align with business goals and technical needs.
Designed, developed, and implemented a robust CI/CD infrastructure with a focus on cost optimization and scalability. Leveraged Jenkins Declarative Pipelines to automate builds, testing, and deployments, ensuring seamless integration and delivery workflows across multiple environments.
Design and Develop Microservices architecture, Microapp architecture, Code coverage, Vulnerability fixes, Application break fixes, Automation, CI/CD, Code hygiene, Code compliance, Cloud migration Onboard and Offboard, Application platform support (GAP, GKS, AWS, lambda S3), Glue, Oracle migration, DevOps implementation, Security enhancements and Ongoing support.
Designed, developed, and implemented a cost-efficient big data pipeline using Python, Apache Spark, and Kafka to handle growing data volumes. The system leverages distributed processing, real-time data streaming, smart partitioning, and resource optimization to ensure high performance and reliability.
Have successfully designed and implemented scalable data processing and analytics solutions to handle huge data, leveraging Terraform, AWS (S3, Glue, Lambda, MSK, Redshift Spectrum), Databricks, and Apache Spark.
Experience in building and deploying applications on to different environments such a QA, UAT and productions.
Managed central repositories and implemented Atlassian stash along with GIT to host GIT central repositories for source code across products, facilitate code reviews and log audits for security compliance.
Automate and Built CICD pipelines on Jenkins and GitHub for cloud native applications and for on premise applications.
Defined dependencies and plugins in Maven pom.xml for various activities and integrated Maven with GIT to manage and deploy project related tags.
Responsible for on boarding application teams to build and deploy their code using GitHub CI/CD, Jenkins and Ansible.
Experience working on deploying and maintaining a production ready, scalable, available and fault tolerant Kubernetes infrastructure.
Managed Maven environment by setting up local, remote, and central repositories with required configuration in maven configuration files.
Rich hands-on in Jenkins - installing, configuring, and maintaining for continuous integration (CI) and for automation of all build and deployments.
Maintained high availability cluster and standalone server environment and refined automation components with scripting and configuration management (Ansible) and experience in writing Ansible scripts.
Experience with designing & building out cloud environments as Infrastructure as Code using Cloud Formation Templates and AWS CDK and Terraform.
Configured and Managed cloud Infrastructure using Amazon Web Services (AWS) including EC2, Auto Scaling, EBS, Elastic Beanstalk, S3, Cloud Front, RDS, VPC, API Gateway, Route 53, Elastic Load Balancer, Cloud Watch, Cloud Formation, SNS, IAM, Optimized volumes and EC2 instances, setting up Security groups & created multi-AZ VPC instances.
Experience with containerization using AWS ECS and AWS EKS.
Designing serverless architecture, scalable and fault-tolerant systems, Microservices architecture.
Successfully facilitated the seamless migration of applications to cloud platforms such as GAP, GKS, AWS, lambda, S3, CloudFormation, Botto3, AWS Steps Machine, Terraform, IaC. Leveraging their expertise in cloud technologies, infrastructure provisioning and application deployment, they enabled businesses to harness the scalability, cost-effectiveness and flexibility of the cloud.
Designed and fortified an identity management system leveraging IAM policies, OAuth2, SSO, SAML, and AWS Cognito to ensure robust access control and authentication. Strengthened data protection by implementing encryption in transit and at rest using TLS/SSL and AWS KMS, complemented by client-side encryption for enhanced security of sensitive workloads. Conducted regular security audits and configuration reviews to maintain compliance with GDPR, HIPAA, and PCI DSS standards. Integrated tools like Raven Scanner, SonarQube, and Web Application Firewalls (WAFs) to proactively identify and mitigate application-level threats. Managed IDS/IPS systems to prevent unauthorized access and potential breaches. Enabled comprehensive security monitoring and traceability by implementing audit trails through AWS CloudTrail.
Develop and implement a very Sophisticated caching mechanism based on Redis. This enhanced caching mechanism should provide improved scalability, availability, and performance for high-traffic applications. It allows for multi-tier caching, Redis Clustering, use of the pub/sub mechanism, and Lua scripting for performing atomic operations.
Engineering and operationalizing advanced-custom Kong plugins with Lua and OpenResty's help for improving API security, traffic management, and request transformation. In developing IP whitelisting, an authentication plug-in, rate-limiting, and log plug-ins, become the best engine available for aimed at capacity, extension, and automation for an API gateway.
Sufficient experience in designing and implementing ACH payments systems in Java with compliance to NACHA (National Automated Clearing House Association) rules and guidelines.
Integrated with major payment processors: Stripe, Square, and Authorize.Net for supports of multiple payment methods including credit/debit cards, ACH, and wallets.
Designed secure payment flows in compliance with PCI DSS standards and holding for TLS/SSL encryption.
Great knowledge in reactive programming with Vert.x, Spring WebFlux, Scala, and Akka, creating event-driven, non-blocking architectures for scalable, highly performant applications. Has wide experience in setting up distributed systems/microservices/real-time streaming solutions with backpressure handling, asynchronous messaging, and highly resilient service orchestrations. Trained in RxJava, Project Reactor, and Akka Streams to implement reactive APIs while ensuring fault tolerance and improving system throughput.
EXPERIENCE: Remote Mar 2024 – Present
Role: Python-Architect DevOps Lead Full Stack Engineer
Client: SLK Holding
Location: Remote N Brunswick NJ
Date: March 2024 – Present
Micro & Macro Businesses and Organizations looking at both transactional and transformational digital solutions because of its core capabilities, great talent, commitment to quality, and the infrastructure to deliver a wide range of technology and consulting. Design and Develop App, Engine and Utility with Standard principles and End to end system Architecture consultancy, Developed Apps, Services and Utility, migration and make it available in cloud environment.
CRAS(CreditRiskAnalysisSystem):
A Credit Risk Analysis System using AI/ML techniques and microservices architecture for real-time inference and prediction offer a scalable, flexible, and efficient way to serve ML models. The ML Or DL model is packaged as a microservice that can be accessed via RESTful APIs for making real-time predictions. This setup decouples the ML model from other components, enabling easier deployment, scaling, and maintenance. Integrated with Kafka for real-time data streaming (new credit applications), where incoming credit data is processed, and predictions are made. Streaming Pipelines for Real-Time ML (Spark Structured Streaming & Kafka) To handle real-time data, we can integrate Kafka for streaming and Spark Structured Streaming to process the data in a scalable manner.
Technical Environment:
Java, Python, Panda, Polar, Ansible, Botto3, Langfuse, Sandbox, Microapps, AWS Steps, Serverless Compute - AWS Fargate, CloudFormation, Dockers, K8s, GAIA (VPC, GCP, GAP, GKP, BigQuery, GKS) and AWS(EC2,S3, AppSync, Vertex AI, SageMaker, Spring AI, Spring Boot, Kong API Gateway, Microservices, OAuth2, GraphQL, Rest API, Open AI, ML, DL, Cloud, PySpark, DataBrick, Spark, Spark MLlib, EMR, SHAP, Multi Tenants Cloud, Data Lake, DPL (Data Pipeline),Dockers, K8s, GIT, Splunk, Swager-API, NodeJS, Express, Automation, Maven, Shell Script, YML, SSL and SSO, Groovy, Shell Script, Helm Chart, Jenkins- Jules (CI/CD), Oracle19, Casandra and Teradata, Redis, ReactJS, Html5, jQuery, JavaScript, Vue JS, Bootstrap, NPM, AEM.
Contribution:
Designed and implemented machine learning (ML, AI) pipelines using Python, Spark, Kafka and Spark MLlib for data preprocessing, feature engineering, model training, and evaluation.
Integrated machine learning models with microservices architecture for real-time inference and prediction using RESTful APIs and OpenAI.
Implemented Azure Active Directory (AAD) for identity management. Azure Key Vault to securely manage application secrets and encryption keys.
Develop and Deployed Kong API Gateway in Kubernetes (K8s), managing API authentication at scale with CI/CD pipelines. Secured APIs with JWT and OAuth2 tokens, enforcing token validation, expiration, and scope-based access control.
Configured Gitlab Runners to use Kubernetes cluster (EKS) to scale up and scale down builds as part of the CI/CD pipeline.
Automated Datadog monitoring configurations via Terraform and Ansible for seamless deployment. Integrated Datadog Synthetic Monitoring to track API and front-end application health.
Configured custom dashboards, alerts, and anomaly detection for proactive system monitoring. Optimized tracing with OpenTelemetry and Datadog APM for performance monitoring across microservices.
Migrated CICD jobs from Jenkins server to Gitlab CICD.
Integrated Amazon Connect with CRM systems (Salesforce, Zendesk) using Lambda connectors and Amazon Lex for AI-powered self-service conversations.
Designed serverless, event-driven architectures using AWS Lambda, Step Functions, EventBridge, and S3 to support IVR flows, call routing, and real-time analytics.
Worked on Creating the Infrastructure using AWS CDK open-source development framework using Typescript and Python to create all types of the AWS resources that were provisioned using CloudFormation Templates.
Worked on Kubernetes container-based deployments using infrastructure as code tools like CDK and Terraform.
Worked with development teams to containerize Java applications using Docker, creating Docker files and managing multistage builds to streamline deployments.
Used Kubernetes to deploy, scale, load balance and manage containers running on AWS Cloud
For an old application, created infrastructure using Terraform and later migrated it to CDK.
Worked on developing an inhouse web application using web development framework such as ReactJS.
Worked on developing lambda functions with runtime as NodeJS to perform automation tasks to support CICD pipelines or to act as modules for CloudFormation.
EXPERIENCE: ONSITE Sept 2022 – Feb 2024
Role: Solution Architect DevOps Tech Lead Full Stack Engineering Manager
Client: JPMorgan Chase & Co.
Location: Wilmington DE
Date: Sept 2022 – Feb 2024
PROJECTS:
1.Consumer and Community Banking – CCB
2.US Wealth Management - USWM – Self Directed Asset Investment – SDAI
Description:
USWM: Cash conversion cycle, US. Wealth Management, Self-directed and automated investing product (SDAI) Actual Assets Under Management (AUM) is this value plus cash (which is not disclosed) J.P. Morgan is introducing the J.P. Morgan Working Capital Index that captures the working capital metrics of the S&P 1500 companies, Portfolio and Performance. When tracked over time, the Index can provide insights into working capital trends that help finance practitioners plan and track the progress of various working capital initiatives within their organizations.
CCB: Primarily under the Chase brand, Consumer and Community Banking (CCB) serves millions of consumers and millions of small businesses with a broad range of financial services including personal banking, credit cards, mortgages, auto financing, investment advice, small business loans and payment processing. Customer can choose how and where they want to bank.
Technical Environment:
Java, Python, Ansible, AWS Steps, AWS MKS, AWS EMR, Serverless Compute - AWS Fargate, Botto3, Sandbox, CloudFormation, Dockers, K8s, GAIA (VPC, GCP, GAP, GKP) and AWS, Spring Boot, Microservices, OAuth2, Cloud, Spark, Multi Tenants Cloud, Data Lake, DPL (Data Pipeline), GIT, Splunk, Spring AI, Swager-API, Automation, Maven, Shell Script, YML, SSL and SSO, Figma, AppSync, Amplify, graphQL, Jenkins- Jules (CI/CD), Groovy, Shell Script, Helm Chart, DataBricks, AEM, Rest API, Oracle19, Casandra and Teradata, Kafka, NodeJS, ReactJS, Vue JS, Html5, jQuery, JavaScript, Bootstrap, NPM.
Contribution:
Configured Elastic Container Service (ECS) capacity Providers auto scaling actions to scale up and scale down based on the number of messages in the SQS.
Worked on Single Sign-on (SSO) Authentication and Authorization framework using AWS Services like Lambda, Cognito, DynamoDB, IAM Role and Identity Providers.
Developed python scripts to update AWS tags from local machine, to check encryption of Kinesis Stream and SQS, inbound rules of the security groups and naming conventions for all the Aws Resources.
Configured Kong API Gateway to enable OAuth2 authentication and protect backend services. Kong Rate Limiting and ACL Plugins to restrict unauthorized access and prevent abuse.
Implemented NodeJS, JSON Schema and Express framework and integrated with Visual Studio Code to ease the effort for the developers to develop CloudFormation Templates in their local.
Migrated application from on-premises to AWS cloud by defining the application as infrastructure as code and was part of the performance testing to fine tune the application.
Developed Python scripts to create a new version of lambda on the deployment of new code and to configure provision concurrency based on the Lambda Version using CloudFormation modules.
Developed custom python scripts for updating the CloudFormation stack and application related parameter store entries in System Manager from Jenkins machine.
Testing the EC2 golden AMIs to make sure the AMI’s has the necessary configuration, agents installed to comply with the industry security best practices.
Developed custom lambda functions of runtime Python to fill send customized alerts to the Prod support team in case of any unusual happenings based on the CloudWatch metrics.
Deployed Spring Boot (Tomcat) microservices as docker containers with AWS Elastic Container Service (ECS) and Elastic Container Registry (ECR) using suitable task placement strategies spanning across multiple availability zones. Implemented Step Scaling policies for service autoscaling in response to number of messages in the SQS.
Worked on Creating the Infrastructure using AWS CDK open-source development framework using Typescript, Python and Botto3 to create all types of the AWS resources that were provisioned using CloudFormation Templates and Terraform.
Led the design and implementation of PCI DSS-compliant solutions to ensure secure handling of payment card data across enterprise systems.
Implemented Role-Based Access Control (RBAC), Multi-Factor Authentication (MFA), and encryption strategies (TLS 1.2/1.3, AES-256) for secure data transmission and storage. Conducted security risk assessments, vulnerability scans, and penetration testing to ensure compliance with PCI DSS Requirement 6 (Develop & maintain secure systems and applications).
Worked on Kubernetes container-based deployments using infrastructure as code tools like CDK and Terraform.
Worked with development teams to containerize Java applications using Docker, creating Docker files and managing multistage builds to streamline deployments.
Used Kubernetes to deploy, scale, load balance and manage containers running on AWS Cloud
For an old application, created infrastructure using Terraform and later migrated it to CDK.
Worked on developing an inhouse web application using web development framework such as ReactJS.
Worked on developing lambda functions with runtime as NodeJS to perform automation tasks to support CICD pipelines or to act as modules for CloudFormation.
Created Kinesis firehose to act as an intermediate platform to forward logs from serverless resources to Splunk and installed Splunk forwarder on the EC2s to forward logs from on-premises applications to Splunk.
Worked on shell scripting to automate system administrator and routing backup jobs.
Monitored overall system performance, performed user management, system updates, disk and storage management environment.
Created Users permissions and assigned the permissions to folder and file structures.
EXPERIENCE: ONSITE Apr 2015 – Sep 2022
Role: Architect-Python-Java (DevOps Tech Lead Sr. Engineer Full Stack)
Client:
CISCO (San Jose CA USA)
AKC – American Kennel Club (RTP NC USA)
RH-Restoration Hardware (Raleigh NC USA)
PROJECTS:
1.MedEvac, Proactive RMA for Intersight Connected Devices (Cisco)
2.BMS (Budget Management System - Cisco),
3.AEM, WEM, CX (Cisco)
4.XMART-Astoria-CMS (XML Modular Authoring and Review Toolkit-Cisco)
5.Online Competition Mgmts. (OCMS-AKC)
6.Order-Bff (Back-end For the Front-end - RH)
7.Order Management Systems (OMS - RH)
8.CCW (Cisco Commerce Workspace)
Description:
1.Intersight leverages telemetry obtained from the connected targets to deliver an enhanced customer experience when the connected targets experience certain failures. Intersight includes the ability to raise a service request
(SR) and a Return Material Authorization (RMA) automatically and authorize the RMA proactively, thus reducing the time from failure to replacement significantly.
2.MedEvac (Proactive RMA): To move to a more Proactive experience for our customers, we will be leveraging our existing connectivity and IC to automatically detect product failures and then auto-create a TAC case and auto-initiate an RMA to a customer. Thereby creating a 100% proactive experience for our customers and fully automated from our end. Automatically detect HW failures on Connected Devices and Automate Replacement process, resulting in significant time savings and reduced customer effort.
Technical Environment:
Python, Java, Ansible/Ansible tower, Action Orchestrator(AO), Command Center, Camunda Workflow BPMN, AI/ML, Panda, Polar, Spark MLlib, NumPy, TensorFlow, PyTorch, Scikit-learn, Fast API, NumPy, Flask, Django, Vertex AI, SageMaker, PySpark, DataBrick, EMR, Serverless Compute - AWS Fargate, Network Orchestrator(NO), SDN, Router, Switches, Gateway, AWS Steps, Java, Go, Caph, Puppet, Docker, K8s, Groovy, Shell Script, Helm Chart Workflow, Camel, Kafka Streaming, Spark data Steaming, Spring Boot, Microservices, OAuth2, CloudFormation, Terraform, Redis, Cloud, Spring AI, Gen-AI, Multi Tenants Cloud, Spark, GIT/Bitbucket, Grafana, Splunk, Fast-API, Boto3, BDB (Big Data and Analytics)Script (Python), Regex and JSON, Kong API Gateway, OpenAPI (Swager-3), Automation, Maven, Shell Script, YML, SSL and SSO, Jenkins, MongoDB, ReactJS, NodeJS, Html5, jQuery, JavaScript, Bootstrap, NPM.
3.Order Management Systems (OMS): An order management system is a software system that facilitates and manages the execution of trade orders, spending, reporting and performance measurement tool built for revenue-driven marketing organizations. Vender/dealers use OMS when filling orders for various types of products and can track the progress of each order throughout the system.
4.Order-Bff (Back-end For the Front-end): It’s a microservice provide API for WISM-UI, WISMO is the ability to answer detailed questions about the lifecycle of a given order in one stop. This includes full lifecycle details, including shipment, delivery and returns, of an order's ship-to, or it's lines, it covers both stocked-items and special purchase order (SPO), purchase order items, with full visibility into all purchase order lifecycle milestones. WISMO answers not only "where" is an order, but also "why" is an order not on time.
5.Order-Capture: Order Capture is an independent microservice application designed to translate the contents of an external order data structure, JSON from Commerce tools in this case and deliver it to CW-Direct for processing.
6.Order-Aggregator: The Microservice is a RESTful API that aggregates Oder service and Purchase Order Service.
Contribution:
Built an event-driven architecture using Kafka and SAGA pattern for order orchestration and consistency. Architected and implemented a scalable, microservices-based e-Commerce platform with high availability using Spring Boot, Kafka, MongoDB, Redis, and Kubernetes. Designed C4 architecture models and applied Domain-Driven Design (DDD) to decompose monolith into Product, Inventory, Order, Payment, and Shipping bounded contexts.
Technical Environment:
Docker, K8s, Couchbase, Kafka, Spring Boot, Microservices, AWS-S3, AWS-SNS, AWS-SQS, GIT/Bitbucket, CW-Direct, Mule, AGT- Commerce tool, JMS, Sumologic, Grafana, Open-API (Swager-3), Apache Maven, Shell Script, YML, SSL and SSO, Okta, Jenkins, MongoDB, ReactJS, Html5, jQuery, JavaScript, Bootstrap, NPM.
7.Budget Management Systems (BMS): is a marketing planning, budgeting, spending, reporting and performance measurement tool built for revenue-driven marketing organizations. Within this tool Marketing leadership teams can plan and capture corporate objectives, lead targets, sales goals and return on investment (ROI) targets. This tool also helps the Marketing operations process to create and manage multiple regional, product-centric and multicurrency global budgets without hassles. This tool enables executives to visualize, analyze and optimize expenditures which aids them to make smarter investment decisions.
Technical Environment:
Docker, Kubernetes, OpenShift, OpenStack, Data Bricks, Kafka, Apache Tomcat, JAVA8, JSP, Servlet, Spring Boot, Microservices, GIT/Bitbucket, Apache Maven, Shell Script, Python, YML, SSL and SSO, RedHat JBoss and Jenkins, IBM uDeploy, VMs, DOMO, OpenShift, CP4I, Informatica ETLs, MongoDB, Camel, Kafka, AngularJS, ReactJS, Html5, jQuery, JavaScript, Bootstrap, NodeJS, Redis, Oracle.
8.XMART-Astoria (XML Modular Authoring and Review Toolkit) - It is currently used by Cisco Technical Documentation writers and sales connect for authoring, conducting reviews, content management, localization and publishing single-sourced content to Cisco.com, Content Management is a software system that provides website authoring, collaboration and administration tools, with Astoria Goals of XMART-Astoria.
The primary goals for XMART (XML Modular Authoring and Review Toolkit) are:
DITA (Darwin Information Typing Architecture): All content will conform to DITA, an open standard of the OASIS committee (http://www.oasis- open.org/committees/dita).
Technical Environment:
JAVA 1.8, J2EE, Spring Boot, Micro Services, Windows Services, Astoria (ECM), XML, ReactJS, MongoDB, Jenkins, Python/Jython, Kafka, Camel, JBoss Fuse, DITA-OT, ActiveMQ, Maven, Tomcat/JIRA/Rally (Issue/Bug Tracking)
9.OCMS-Online Competition Management System: The Online Competition Management System (OCMS) is one of the AKC's two competition (dog show) management systems. AKC member clubs hold over 30,000 events per year and the AKC offers OCMS as one way to assist the clubs in planning these events, as well as capturing the event results. These results are then passed to backend processing to determine titles to be awarded to event competitors. OCMS is a service-based web application. The second system, Competition Management System (CMS, also known as "Classic") is a PowerBuilder-based client-server application. Both OCMS and CMS use the same system of record (database) and can (for the most part) interoperate on the same events. The long-term goal of OCMS is to replace CMS.
Technical Environment:
JAVA 1.7/1.8, J2EE, Spring/Spring boot, Microservices, Web Services (JAX-RS - Restful Web Services JAX-WS), Hibernate, Drools, RMI, OpenShift, CP4I, XML, ORACLE (PL/SQL), JVMC, Steal JS, Angular JS, Tomcat, Jenkins, Groovy, Shell Script, Helm Chart Phabricator, OnBase, JIRA, Camel, Kafka, AWS Cloud Migration, Gitlab, SVN and Maven.
Contribution:
•Requirements gathering, scoping and risk analysis of major system changes and enhancements.
•Collaboration and communication between development and operations teams to ensure that software development and deployment processes run smoothly.
•Involved in gathering business requirements from the client for projects/releases/new/new enhancements/new developments.
•Designed and implemented Datadog APM (Application Performance Monitoring), Infrastructure Monitoring, and Log Management for microservices running on AWS (EKS, Lambda, EC2, S3, MSK).
•Integrated Datadog Agent for real-time telemetry collection, system metrics, and distributed tracing. Implemented Datadog Log Management using log forwarding from AWS CloudWatch, Fluentd, and Kubernetes DaemonSet for centralized log aggregation.
•Integrated VTEX modules (Catalog, Checkout, Promotions, Order Management) with Contentstack, enabling scalable and flexible content-driven commerce.
•Coding and configuration to ensure delivery of a module.
•Designed and implemented enterprise-grade integrations using TIBCO Active Matrix Business Works, enabling seamless message routing, transformation, and real-time data processing. Developed and deployed API-led integrations using MuleSoft Anypoint Platform, optimizing system interoperability, message orchestration, and cloud-native connectivity.
•Customized Dockerfiles and
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