Vinod Kumar Nair

About Vinod Kumar Nair

Technology Leader and AI Architect with 17 years of experience building AI-native platforms and large-scale cloud infrastructure from the ground up. Has led government digital transformation programs across Saudi Arabia, Singapore, and the UK. Certified in Agentic AI, with hands-on production expertise in AI, RAG systems overseeing $5.2T in Assets Under Management & a public speaker at global conferences. AI & Platform InnovationI specialize in building Generative AI ecosystems and Agentic AI solutions that drive measurable productivity.1. AI Strategy: Architected \"Florence,\" a secure internal ChatGPT-like platform for 800+ developers, and \"Themis,\" an AI agent utilizing RAG and AWS Bedrock for automated service ticket resolution.2. Engineering Productivity: Automated AI code reviews on GitLab using Claude Code, saving manual hours annually and improving developer productivity by 25-35%.3. SaaS at Scale: Standardized developer onboarding across 80+ teams, reducing the cycle from days to a single day. Cloud-Native & Infrastructure ExpertiseAs a CNCF Kubestronaut and AWS-certified professional, I focus on cost-efficient, secure, and resilient distributed systems.1. Cost Optimization: Championed AWS Graviton, Karpenter, and distroless containers, slashing compute and storage costs by 25-30%.2. Security & Reliability: Implemented Zero-Trust architecture and optimized observability via Datadog, reducing false alert noise by 60%.3. Global Delivery: Extensive experience delivering enterprise solutions in Singapore, the UK, and Saudi Arabia for clients like ANZ Bank, Lloyds Banking Group, and LTA (Land Transport Authority). Community & Lifelong LearningI am a recognized industry ambassador and public speaker, frequently sharing insights at KubeCon, AWS Community Days, KyvernoCon, and HashiTalks. I am currently pursuing an M.S. in Computer Science at Georgia Tech (OMSCS) to further deepen my expertise in AI and distributed systems. Core Tech Stack: Programming Languages - Python, Java, JavaScript, TypeScript, SQLAI/ML & Generative AI - AWS Bedrock, Anthropic Claude, OpenAI, RAG, LangChain, LangGraph, SageMakerData & Vector Databases - Opensearch, S3 Vector, PineconeFrameworks & Libraries - Fast API, Spring, OpenAPICloud & Infrastructure - AWS (Graviton, SNS, SQS, ECR, EKS), Kubernetes, KubeFlow, KEDA, IoT, KafkaDevOps & CI/CD - Docker, Kubernetes, ArgoCD, ArgoWorkflow, Terraform, DevSecOps, Cilium, CI/CD PipelinesProtocols & APIs - REST, GraphQL, gRPC, WebSocket, MQTT, HTTP, TCP/IP, GraphQL

Experience

1. Principal Engineer

   Arcesium

   Feb 2022 — Present · Bengaluru, IN

   Led firmwide Artificial Intelligence, platform engineering, cost optimization, and reliability initiatives. Influenced senior leadership, work with cross-functional stakeholders, define the roadmap in GenAI Initiatives and its implementation in enterprise AI adoption. Provided technical leadership across cross-functional stakeholders including Product, UX, and Platform teams to integrate AI capabilities into enterprise SaaS systemsKey Contributions & Achievements(1) AI Innovation at Scale:Architected an internal ChatGPT-like platform on AWS Bedrock, enabling 800+ developers with secure AI coding assistance and boosting productivity by 25–35% while ensuring compliance.Championed AI-driven IDE adoption (Cline AI + Bedrock), improving developer productivity by 20–35% firmwide.Implemented AI Agents with OpenAI LLMs + MCP server, automating GitLab MR reviews and ticket resolution, saving hours annually across MRs.(2) Cloud Cost & Security Optimization:Drove adoption of distroless + ephemeral containers, cutting image sizes by 70% and reducing storage/egress costs by ~20%.Led JDK 21 upgrade & Jakarta EE migration across 200+ applications, eliminating vulnerabilities and meeting regulatory mandates.Championed AWS Graviton + Karpenter + pod-aligned S3 buckets, cutting compute/storage costs by 25–30% with performance gains.(3) Developer Experience & Reliability:Standardized GitLab CI/CD pipelines firmwide, reducing onboarding from several days to a single day.Enhanced observability with Datadog, reducing false alerts by 60% and improving on-call stability.Introduced Argo Workflows for low/no-code data engineering pipelines, cutting pipeline build time from 3 days to 1 day.(4) RecognitionArcesium Tech Contributor Award (2022, 2023) – for firmwide technical leadership & innovation.Active speaker at KubeCon, HashiTalks, AWS Community Days; contributor to open-source and technical blogs.

Education

• St. John's School (CBSE)

  XII, Science

  2003 — 2004

• Maharshi Dayanand University

  BE, IT

  2004 — 2008

• St. John's School (CBSE)

  XII, Non-Medical

  2001 — 2002

• Georgia Institute of Technology

  Master of Science - MS, Computer Science

Skills

• Portal Development
• Javaserver Pages (Jsp)
• Cxf
• Unix
• Amazon Web Services (Aws)
• Spring
• Servlets
• Devops
• Ant
• Jms
• Jax-Ws
• Java
• Struts
• Soapui
• Microservices
• Xml
• Rest
• Jboss Application Server
• Unix Shell Scripting
• Sql
• Restful Webservices
• Hibernate
• Oracle
• Pl/Sql
• Jquery
• Json
• Apache Cxf
• Weblogic
• Jsp
• Maven
• J2ee Application Development
• Core Java
• D3.js
• Soa
• Java Enterprise Edition
• Web Services
• Mongodb
• Sun Certified Java Programmer
• Liferay
• Javascript