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chethanuk/README.md

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🔭 I am a seasoned Staff AI/Data Engineer who architects resilient, scalable agentic workflows, data pipelines, and Data/ML infrastructure in a cloud-native stack. I specialize in bridging the gap between experimental AI and production-grade infrastructure for global startups. I design and implement ultra-reliable, low-latency systems that power real-time analytics engines and agentic workflows.
Primarily, I orchestrate autonomous AI agents, multi-agent systems, and advanced RAG pipelines. Leveraging the latest advancements in agentic workflows, I focus on complex Prompt Engineering and developing custom Claude code plugins. I am also an expert in data engineering workflows—both real-time and batch data pipelines—plus LLM orchestration, machine learning pipelines, and MLOps infrastructure. I specialize in production-grade AI systems, data pipelines, and cloud-native infrastructure that solve complex challenges for global startups.

Also, actively contributing to Apache Airflow, Apache Pinot and other open-source projects - and recently in the last 2 years into LLM and AI agentic workflows [Claude Google Gemini].

"You have to dream before your dreams come true."

⚡️ Fun fact: I'm a huge fan of FC Barcelona, and I love traveling, hiking, and gaming on Xbox. Please feel free to connect with me on X (Twitter) Follow or Linkedin: ChethanUK.

Technical Skills & Tools

  • Big Data & Data Engineering:
    Apache Flink ApacheSpark Databricks Snowflake Apache Airflow Apache Kafka AWS Kinesis TrinoDB ApacheBeam

  • DataOps (Data DevOps):
    Kubernetes Docker Terraform mlflow

  • Languages & Frameworks :
    Python Go Rust FastAPI PyTorch CUDA Google Gemini Claude

  • AI Cloud:
    Google Cloud AWS Microsoft Azure Alibaba Cloud Fly.io Cloudflare

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Open Source Contributions

Details > 50+ merged PRs across 16+ organisations and many others over the last 7+ years
  • Big Data and Data Frameworks Apache Airflow Apache Pinot Apache Beam Flink K8s Operator

  • AI / ML vLLM AIBrix CentralMind Gateway PingCAP AutoFlow Open WebUI MCPO Swarms

  • Data Infrastructure Kubeflow Spark Operator Trino KubeFlow ZenML KONG DAPR SDKMAN

  • Cloud Google Tunix Data on EKS python-deequ Google Cloud Dataproc

What I've Been Doing Recently ⚙️

I orchestrate autonomous AI agents, multi-agent systems, and advanced RAG pipelines. Leveraging the latest advancements in agentic workflows, I focus on complex Prompt Engineering and developing custom Claude code skills and plugins.

  • AI Architect: I design and implement ultra-reliable, low-latency systems that power real-time analytics engines, agentic workflows, and live data ingestion.
  • Real-Time Data Pipelines & AWS Infrastructure: I architect and maintain high-scale, cloud-native streaming solutions leveraging Amazon Kinesis and MSK (Managed Kafka) to handle millions of events per second. By utilizing Terraform/CDK for Infrastructure as Code and CloudWatch/OpenSearch for deep observability, I ensure that real-time ingestion pipelines remain resilient, schema-consistent, and highly available across complex AWS environments.
  • AI Architect & Strategic Technical Leadership: I spearhead architecture and technical design for next-generation products, specifically focusing on agentic workflows and specialized systems for high-frequency data storage and replay. I bridge the gap between non-deterministic AI outputs and the rigid reliability required for financial and analytical data replay systems.
  • Performance Optimization & Scalability: I obsessively optimize existing services for maximum throughput and minimal latency. This includes refining data ingestion services, stream processing pipelines, and Big Data warehouses (Snowflake/ClickHouse), alongside tuning container-based microservices (ECS/EKS) to ensure seamless horizontal and vertical scaling under heavy production loads.
  • Claude Agentic Orchestration & Skill Development: I design and implement advanced autonomous systems using the Claude Agent SDK, building custom Claude Skills and Claude Plugins to extend LLM capabilities into real-world actions. By architecting multi-step Claude Agentic Workflows, I enable seamless tool-calling and sophisticated reasoning cycles, allowing AI agents to navigate complex, non-deterministic tasks while maintaining strict operational guardrails and enterprise-grade reliability.
  • 🧹 Vibe Code Cleanup: As AI drastically accelerates initial code generation, I specialize in transforming fragile, AI-generated "vibe code" into secure, decoupled, and scalable enterprise systems. I audit, refactor, and harden these prototypes so they are robust enough for production and real-world traffic.

I get excited about opportunities where I can leverage big data to discover insights and identify patterns that have real human impact.
I love connecting with new people. Give me a shout at chethanuk@outlook.com or on Linkedin: ChethanUK!


github contributions

GitHub Streak

Activity Graph

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  1. Computer-Vision---Facial-Keypoint-Detection Computer-Vision---Facial-Keypoint-Detection Public

    Computer Vision - Facial Keypoint Detection

    HTML

  2. Lane-Finding-using-Computer-Vision Lane-Finding-using-Computer-Vision Public

    Lane Finding using Computer Vision

    HTML

  3. apache/pinot apache/pinot Public

    Apache Pinot - A realtime distributed OLAP datastore

    Java 6k 1.5k

  4. AI-Agent-to-solve-Sudoku AI-Agent-to-solve-Sudoku Public

    Created an AI to solve Diagonal Sudokus using constraint propagation and search techniques. Additionally, taught the agent to use the Naked Twins advanced Sudoku strategy.

    Python 1

  5. apache/airflow apache/airflow Public

    Apache Airflow - A platform to programmatically author, schedule, and monitor workflows

    Python 44.5k 16.6k