Suryaday Nath
@suryadaynath
Enterprise AI Architect with 8+ years building governed, cost-disciplined GenAI and agentic platforms for enterprises.
IndiaWhat I'm looking for
I’m an Enterprise AI Architect with 8+ years bridging production-grade GenAI engineering and executive strategy. I design multi-persona AI Agents (RAG + Agents + LLMs) and deliver GenAI roadmaps and enterprise readiness assessments that directly influence AI investment decisions, including $2M+ in cloud/AI commitments.
My approach blends technical architecture with FinOps-driven cost discipline and rigorous governance. I’ve reduced retrieval time by 40% through semantic RAG, structured metadata and canonical data models to improve enterprise search quality, and enforced strict LLM API governance while building secure AWS/Azure landing zones and disaster recovery foundations. I’m seeking AI Architect roles where I can align technical architecture with measurable business value—so enterprise AI stays profitable, secure, and governed.
Experience
Work history, roles, and key accomplishments
Built GenAI roadmaps and enterprise readiness assessments for C-suite stakeholders, influencing $2M+ in cloud/AI investment decisions. Engineered multi-persona agentic RAG solutions indexing 500+ documents and cutting retrieval time by 40% (recovering 15+ hours/month per user), with FinOps-governed and secure AWS/Azure landing zones.
Led AWS/Azure cloud transformation programs for BFSI and large enterprises, defining target-state architectures, migration strategies, and modernization roadmaps. Delivered cost optimization reducing client cloud spend by 20–35% and operationalized cloud governance and FinOps frameworks across multi-account environments.
Designed robust Infrastructure-as-Code (IaC) frameworks using Terraform and CI/CD pipelines, reducing manual infrastructure provisioning time by 40%.
Executed high-volume automated QA and load-testing campaigns for a major European telecom customer. Built an AI-powered Terraform infrastructure engineering platform that converts natural-language requirements into dependency-aware, schema-grounded IaC using hybrid RAG, DAG-based generation, anti-hallucination validation, and eval-driven regression (85%+ terraform validate pass rate).
Education
Degrees, certifications, and relevant coursework
T.A. Pai Management Institute (TAPMI)
Master of Business Administration, Marketing & IT
2018 - 2020
Grade: CGPA: 6.08
Earned an MBA with a focus on Marketing & IT from TAPMI between 2018 and 2020 (CGPA: 6.08).
Kalinga Institute of Industrial Technology (KIIT)
Bachelor of Technology, Electronics & Instrumentation
2010 - 2014
Grade: CGPA: 8.25
Completed a B.Tech in Electronics & Instrumentation at KIIT from 2010 to 2014 (CGPA: 8.25).
Availability
Location
IndiaAuthorized to work in
Salary expectations
Social media
Job categories
Skills
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