About me (Registered since 26/10/2025)

Mohammed Rohith S is a Singapore-based AI Infrastructure Architect and MLOps/AgentOps Engineer with over 6.7 years of experience in designing secure, scalable, and explainable AI systems across healthcare, logistics, and government sectors. With a strong foundation in cloud-native engineering, operational AI governance, and intelligent automation, he specializes in building platforms that align artificial intelligence with business value, compliance, and human trust.

Rohith’s career spans major enterprises including Wipro, Cognizant, and DHL (via Encora), where he led critical transformations in ML lifecycle automation, model governance, and real-time inferencing using Azure ML, GCP Vertex AI, and Kubernetes-based microservices. His core strength lies in orchestrating complete AI infrastructure layers-from data validation, CI/CD pipelines, vector-based retrieval (FAISS/ChromaDB), to GenAI explainability (SHAP, LIME), all while embedding traceability, RBAC, audit logging, and policy-aware design.

At the forefront of GenAI adoption, he has pioneered modular systems integrating LangChain, RAG pipelines, agent memory, and multi-agent orchestration (AutoGen, LangGraph). His capstone system-an AI-driven fraud detection framework-showcases end-to-end AgentOps execution using FastAPI, Streamlit, LangChain, and secure prompt handling for enterprise explainability.

Rohith’s vision goes beyond engineering – he is a systems thinker. His roadmap includes establishing a Responsible AgentOps Lab in Singapore, contributing to AI governance initiatives, and advising enterprises and governments on compliance-first AI adoption. He is currently focused on scaling reusable AgentOps frameworks aligned with Singapore’s AI Strategy 2.0 and IMDA’s AI Verify ecosystem.

A proactive contributor to the global AI community, he engages with open-source, publishes infrastructure blueprints, and mentors emerging engineers. He brings a unique cross-section of domain, delivery, and depth-able to design, implement, and evolve operational AI ecosystems for real-world impact.

“I don’t just deploy intelligence. I design infrastructures where intelligence evolves, adapts, and earns trust.”

Skills

Tech Skills

Portfolio

Education

Key Skills and Competencies

AI Infrastructure, MLOps, LLMOps, AIOps, AgentOps, Cloud-Native Engineering, LangChain, Vertex AI, Azure ML, MLflow, AutoGen, LangGraph, FAISS, ChromaDB, SHAP, LIME, DiCE, FastAPI, Streamlit, GitOps, Kubernetes, Docker, Model Observability, RAG Pipelines, Prompt Engineering, Secure Prompt Handling, RBAC, Data Validation, CI/CD for ML, Explainable AI, Policy-Aware System Design, Responsible AI, AI Governance, AI Compliance (HIPAA, PDPA, GDPR), Audit Logging, AI System Orchestration, Infrastructure as Code, Multi-Agent Systems, Open-Source Contributions, System Thinking in AI

Work Experience

Languages

English
Professional

Certifications & Licences