About me

I am Akshaya Sunkari, an AI and Cloud Engineer with 2+ years of experience designing, deploying, and operationalizing secure and scalable AI solutions on the cloud. I specialize in Azure AI, with hands-on experience building LLM-powered applications, RAG pipelines, and agentic AI workflows, alongside prompt engineering, model fine-tuning, and vector databases. My work spans end-to-end MLOps — automating with Python, containerizing and orchestrating with Docker and Kubernetes, and building CI/CD pipelines with Azure DevOps and GitHub Actions to take models from prototype to production. I focus on designing resilient, intelligent systems that improve deployment efficiency and operational stability.

In addition to my AI and cloud experience, I have a strong interest in problem-solving, backed by my background in software development and infrastructure automation. I enjoy tackling complex technical challenges and continuously seek opportunities to build solutions that drive performance, scalability, and real-world impact.

My skills

  • Generative AI & LLMs
    80%
  • Cloud Computing
    90%
  • MLOps & Model Deployment
    80%
  • Machine Learning
    70%
  • DevOps & CI/CD
    80%
  • Python & Software Development
    75%

Resume

Education

  1. Arizona State University

    Masters in Computer Science 2022 - 2023

    Activities and societies: Teaching Assistant for CSE 575: Statistical Machine Learning course.
    Relevant Coursework: Foundations of Algorithms, Distributed Database Systems, Statistical Machine Learning, Data Mining, Software Requirements and Specifications, Software Verification, Validation and Testing, Software Security, Information Assurance and Security

  2. Amrita Vishwa Vidyapeetham

    Bachelors in Computer Science 2017 - 2021

    Activities and societies: Member of amFOSS(FOSS@Amrita) club
    Relevant Coursework: Object Oriented Programming, Data Structures, Database Management Systems, Data Science, Deep Learning, Big Data, Operating Systems, Computer Networks, Software Engineering, Computer Architecture

Experience

  1. Cloud and AI Engineer

    Cloud 9 Infosystems June 2024 - Present

    - Built and deployed LLM-powered applications and RAG pipelines on Azure AI / AI Foundry, integrating vector databases for retrieval, grounding, and semantic search
    - Developed agentic AI workflows and applied prompt engineering and model fine-tuning to improve accuracy and reliability of production AI systems
    - Operationalized end-to-end MLOps pipelines in Azure DevOps and GitHub Actions, automating model build, evaluation, testing, and deployment with blue-green release strategies
    - Containerized AI/ML services with Docker and orchestrated them on Azure Kubernetes Service (AKS), scaling inference workloads while cutting infrastructure costs by nearly 50%
    - Designed and deployed secure, highly available Azure infrastructure to serve AI/ML workloads with 99.99% uptime, using Virtual Machines, Azure SQL Database, Load Balancer, Blob Storage, and Virtual Network
    - Automated model deployment, provisioning, and resource optimization using Python, reducing manual effort and accelerating release cycles
    - Monitored model and application performance through Azure Monitor, Application Insights, and Log Analytics, enabling faster detection of model failures and performance degradation
    - Implemented Infrastructure as Code with Terraform and ARM templates for reproducible model training and serving environments
    - Built a Disaster Recovery strategy with automated backups and cross-region failover, achieving a 2-hour RTO and 15-minute RPO for business-critical AI services

  2. Software Engineer (Cloud and Data Focus)

    Tetra SystemsMarch 2024 - June 2024

    - Engineered a scalable distributed computing service using Apache Spark and Hadoop, managing 500 nodes to handle large-scale data workloads, and automated task management, significantly reducing manual effort.
    - Enhanced data processing pipelines with Apache Spark, extracting and transforming data from the Hadoop Distributed File System (HDFS), achieving a 35% improvement in data retrieval times through effective schema design.
    - Designed and maintained Java Spring-based microservices for complex data processing tasks, applying object-oriented design principles.

  3. Teaching Assistant

    Arizona State UniversityJanuary 2023 - October 2023

    As a Teaching Assistant at Arizona State University, I supported Professors YooJung Choi and Mohammed Reza in teaching CSE 575: Statistical Machine Learning. My responsibilities included conducting office hours, coordinating assignments, and providing valuable assistance to 150 students.

  4. System Software Engineer

    Cerner CorporationMay 2021 - Decemeber 2021

    - Redesigned the Feature Tracking Application using Spring Boot and MySQL and containerized it with Docker for deployment on internal Kubernetes clusters hosted in an on-premise data center
    - Developed Python scripts to automate monitoring tasks and environment readiness checks, integrating outputs into internal Grafana dashboards powered by Prometheus
    - Improved CI/CD reliability by optimizing Jenkins pipelines using Groovy and YAML
    - Built React dashboards with Redux to visualize uptime and API performance using custom metrics collected from internal logging services and Prometheus endpoints
    - Contributed to VM provisioning automation for dev/test environments and collaborated with infrastructure teams on virtual network peering and DNS routing for service exposure within the data center

  5. System Software Engineer Intern

    Cerner CorporationJanuary 2021 - May 2021

    - Developed Python scripts to automate domain builds and refreshes, resulting in a 50% reduction in execution times and enhancing overall system efficiency.
    - Enhanced Selenium-based test automation frameworks, leading to a 20% reduction in critical defects through comprehensive unit and integration testing.