Portfolio
Building the Future
Designed to Scale
About Me
Hello, I'm Sujith Somanunnithan — a Digital Solutions Architect with 18+ years of experience engineering enterprise-grade systems across Cloud, AI, and Platform Modernization domains. I specialize in translating complex business objectives into scalable, secure, and intelligent digital ecosystems.
My core focus areas include:
- Cloud Strategy & Architecture: Driving cloud adoption, platform engineering, and landing zone setup across AWS, Azure, and GCP, with strong emphasis on CI/CD, governance, and compliance.
- Applied Generative AI: Delivering LLM-powered automation across enterprise platforms using RAG, agentic frameworks, and context-aware orchestration, aligned to responsible AI practices.
- AI/ML & Computer Vision: Architecting end-to-end ML and vision AI pipelines, from model development and MLOps to deployment across edge and multi-cloud environments.
- Legacy Modernization: Transforming Mainframe and AS400 estates into agile microservices, leveraging replatforming and reengineering strategies with zero-downtime migration.
- Data Engineering & RAG Systems: Building modern data lakehouse platforms, real-time ingestion pipelines, and RAG-enabled knowledge systems using vector search and semantic retrieval.
With deep technical expertise in platform design, AI orchestration, and data strategy, I bring a pragmatic, future-ready approach to every initiative. My mission is to architect autonomous, data-driven enterprises that scale with confidence and deliver real-world impact — one architecture at a time.
18+
Years Experience
AI, Cloud, & Modernization
Core Technology Domains
Professional Journey
Education
MSc in Data Science and BigData
DSTI Paris, France
Bachelor of Technology in Electronics & Communication
Anna University Chennai, India
Experience
Senior Solution Architect
Deloitte Consulting, Germany
Leading cloud transformation and AI implementation projects
Senior Solution Architect
Marina Bay Sands, Singapore
Design and implementing Gaming, Retail and Hospitality Solutions
Software Engineer, Lead Programmer
Various
Design and Development of Enterprise solutions
Contact me for the Detailed CV and Project details
Skills & Expertise
Cloud Architecture & Engineering
Data Architecture & Engineering
Applied Generative AI & Agents
AI/ML & Computer Vision
Legacy Modernization
Programming & Platforms
Featured Projects
Due to the breadth and confidentiality of enterprise engagements, detailed project listings are not displayed here.
Contact me for a personalized overview.
Certifications
TOGAF
TOGAF 9.2 Certified Architect
Azure
Solutions Architect Expert
Azure
Cloud Administrator
GCP
Cloud Architect Professional
GCP
Professional Network Engineer
GCP
Professional Security Engineer
AWS
Solutions Architect Professional
AWS
Advanced Network Specialty
AWS
Security Specialty
AWS
DevOps Engineer Professional
AWS
Machine Learning Specialty
Azure
Microsoft Certified: Azure AI Engineer Associate
neo4j
Neo4j Certified Professional
AWS
AWS Certified Solutions Architect – Associate
AWS
AWS Partner: Digital Sovereignty
kubernetes
CKA: Certified Kubernetes Administrator
Solutions & Services
Cloud Architecture
Architect and implement robust, scalable, and secure cloud platforms that align with enterprise IT and business goals.
- Cloud adoption strategy, business case development, and operating model design
- Landing Zone setup on AWS, Azure, and GCP with multi-account governance
- CI/CD pipeline design and implementation using GitOps, Azure DevOps, CodePipeline, etc.
- Platform engineering for reusable, compliant cloud environments and developer productivity
- Security, identity, and policy management aligned to enterprise compliance needs
Applied Generative AI
Design and integrate Large Language Model-based solutions across enterprise systems to enable intelligent, context-aware automation.
- LLM integration with CRMs, ERPs, and internal platforms
- Retrieval-Augmented Generation (RAG) frameworks for contextual precision
- Agentic AI systems for autonomous task orchestration
- Enterprise-grade prompt engineering and fine-tuning strategies
- Compliance, observability, and responsible AI governance
End-to-End ML Solutions
Deliver robust machine learning systems from data strategy to production, ensuring scalable, secure, and insight-driven outcomes.
- ML use case discovery, feasibility analysis, and business alignment
- Model development using TensorFlow, PyTorch, XGBoost, and scikit-learn
- Automated training pipelines with feature stores and model versioning
- MLOps implementation using SageMaker, Azure ML, MLflow, and CI/CD
- Real-time and batch inference deployment with monitoring & retraining
Legacy Modernization: Mainframe & AS400
Transform legacy Mainframe and AS400 workloads into modern, agile cloud-native architectures for long-term scalability and innovation.
- Pre-migration assessment including workload discovery, dependency mapping, and technical feasibility
- Code analysis and classification for RPG, COBOL, JCL, and DB2 workloads
- Refactoring or replatforming using AWS Mainframe Modernization, BluAge, and Azure tools
- Re-architecting into containerized microservices with Kafka/event-driven or REST-based integrations
- Data offloading and modernization using S3, PostgreSQL, or Snowflake
- Zero-downtime migration strategies, CI/CD enablement, and operations transition planning
Cloud Migrations
Execute secure, cost-optimized cloud migrations across application, data, and infrastructure layers with minimal disruption.
- Cloud readiness assessments including application profiling, TCO analysis, and migration planning
- Design of migration strategy: lift-and-shift, replatforming, or re-architecture
- Landing zone setup with governance, identity, networking, and security controls
- Execution using Azure Migrate, AWS Migration Hub, or GCP tools
- Data migration pipelines and synchronization with legacy systems
- Post-migration optimization for performance, cost, and resilience
Computer Vision Solutions
Deliver end-to-end vision AI platforms leveraging cloud-native and open-source technologies for real-time and batch processing of visual data.
- Model development for classification, detection, and segmentation using PyTorch, TensorFlow, and ONNX
- Cloud-native integration using AWS Rekognition, Azure Cognitive Services, and Google Vision AI
- Custom pipelines for OCR, document parsing, and anomaly detection using Tesseract, OpenCV, and Transformers
- Deployment on edge, hybrid, or multi-cloud environments for scalable real-time inference
- Use cases across healthcare, manufacturing, retail, and security with robust MLOps pipelines
AI Agents & Orchestration
Build scalable, goal-driven agentic systems that integrate with enterprise applications to automate tasks, optimize workflows, and support decision-making.
- Design and deployment of autonomous agents using LangGraph, CrewAI, and AutoGen
- Multi-agent orchestration for task decomposition, collaboration, and execution
- Real-time integrations with internal APIs, ERP/CRM systems, and cloud platforms
- Secure sandboxing and guardrails for constrained and compliant agent actions
- Agent memory and tool chaining for context-aware task automation
RAG-Enabled Knowledge Systems
Deliver Retrieval-Augmented Generation (RAG) pipelines that unlock contextual, domain-grounded insights from enterprise knowledge bases.
- Architecture and deployment of RAG systems combining LLMs with vector databases
- Ingestion and preprocessing of enterprise documents, PDFs, and structured data
- Embedding and chunking strategies optimized for semantic retrieval
- Vector store integrations with FAISS, Weaviate, Pinecone, and Azure Cognitive Search
- Fine-tuned grounding logic to align output with domain-specific compliance needs
Data Architectur & Engineering
Design and implement resilient, scalable data platforms to power analytics, AI, and operational insights.
- Modern data lakehouse architecture using Delta Lake, Iceberg, or BigLake
- ETL/ELT pipelines using Azure Data Factory, AWS Glue, Apache Airflow, Snowflake and Databricks
- Batch and real-time ingestion using Kafka, Kinesis, Pub/Sub, and Apache Flink
- Data modeling, partitioning, and performance optimization for BigQuery, Snowflake, Synapse, and Redshift
- Data quality, cataloging, and lineage using tools like Great Expectations and OpenMetadata