Solution Architect, Enterprise Architect

Summary

Establish Architecture, Design, technology principles and guidelines.
Defining enterprise portfolio roadmaps, build strategy to reduce costs in IT and collaborate with various stakeholders from business, IT, operation partners and vendors to define enterprise architecture blueprint.
Lead the strategy and architecture of transforming large enterprise scale platforms from legacy implementation to modern architecture with continuous modernization and tech stack.
Solution Architecture, E2E System and Application Design(HLD, LLD), Solution Research, delivering product PoC and advanced automations.
Leading Development for Cloud Native Applications with design principles.
MLOps strategies and Implementation across Machine Learning products.
Development of Large Language Models with LangChain and LLMOps
Building centralized Datalake and ETL with Customer Data Platform(Snowflake)
Design and Implementation of Customer Behavior Analytics tool.
Implementing data pipelines, Data Modelling and Master Data Management
Design E2E Cloud Infrastructure, data storage and monitoring, logging, advanced automation and security with SAST and DAST
Setting up IaC pipelines using Terraform and CICD via Jenkins
Full Stack Application Development leveraging appropriate design patterns.
Design code structure, Code Reviews and Git Source Code Management
Service Oriented Architecture, Event Driven Architecture, Microservices Driven Architecture, Domain Driven Design
Design E2E Infrastructure(GCP/AWS/Azure), Networking, Security, Databases, Storage, Compute, Serverless and advanced automation.
Design advance monitoring, logging, and high availability solutions.
Delivering Microservices based solutions in Kubernetes Clusters with E2E automated setup using CI/CD in cloud and on-premise setups.
IaC with Terraform and Configuration management using Ansible
MLOps data pipeline design using Airflow, Kubeflow, MLFlow, VertexAI
Developing Anomaly detection, forecasting (classification and regression) based models using Tensorflow(Autoencoders), XGboost(Gradient Boosting), Pytorch on IOT platforms.
Datalake setup and Develop data compliance models and security (Threat Modelling) across products and enterprises

Expectations

Enterprise and Solution Architecture

Employment Preferences

Expected Base Salary

*,*00,000 INR

Experience

Skills

• Solution Designing
• Integrations
• Configurations
• Systems
• Domain
• Insurance
• IOT
• BSS
• OSS
• AR
• VR
• AI
• ML
• CMS
• CDP
• PCRF
• IMS
• Operating Systems
• Linux
• Unix
• RHEL
• Ubuntu
• Microsoft Windows
• Cloud Platforms
• AWS
• VSphere
• Azure
• GCP
• OpenStack
• CRM
• ITSM Tools
• Salesforce
• Comverse CC
• Service Now
• Amdocs CIM
• BMC Remedy
• Development
• Testing
• Operations
• Front End
• HTML
• CSS
• JavaScript
• ReactJS
• Angular
• Unity3D
• Backend
• Python
• Flask
• Django
• Java
• Shell Scripting
• PLSQL
• Groovy
• SQL
• Databases
• Postgres
• MySQL
• Oracle
• Casandra
• MongoDb
• Redis
• InfluxDb
• DevOps
• Kubernetes
• Docker
• Jenkins
• Ansible
• Gitlab
• Terraform
• Stream Processing
• Kafka
• Pravega
• Kinesis
• Data Science
• TensorFlow
• Keras
• Pytorch
• XGboost
• Autoencoders
• LLM
• ML-Ops
• DataOps
• Airflow
• Kubeflow
• VertexAI
• TFX
• ML-Flow
• Glue
• Spark
• Testing Tools
• Postman
• SOAP UI
• Wire-Shark
• Selenium
• Management
• Business Process Framework
• Methodologies
• Agile
• Scrum
• Kanban
• TOGAF
• ETOM
• ITIL
• Waterfall
• Lean
• TM Forum
• Management Tools
• Microsoft Project
• Smartsheet
• MS-Office
• Atlassian Jira
• Confluence