Cloud-Native Software Engineer with 3 years of professional experience, specializing in building C#, Java applications, designing multi-cloud solutions with AWS & GCP, and leveraging Kubernetes orchestration for scalable deployments.
I enjoy exploring LLMs (Large Language Models) by integrating them with Retrieval-Augmented Generation (RAG) systems to tackle complex challenges. Constantly experimenting with new technologies, I actively use Go for innovative projects and an active member of the Cloud Native Computing Foundation (CNCF). I also spend time on platforms like Hacker News to stay informed about the latest tech advancements.
A CVE (Cybersecurity Vulnerabilities) Insights Platform leveraging LLM's to help users secure their devices, detect vulnerabilities early, and adapt to emerging cyber threats. This platform offers high reliability and a user-friendly interface, powered by real-time processing and scalable infrastructure. A production-ready solution to mitigate LLM data staleness and hallucinations by automating continuous vector database updates, ensuring accurate and up-to-date embeddings.
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RAG Chatbot: Designed and Developed a Retrieval-Augmented Generation (RAG) Chatbot using Llama-3.1-8b(an Open Source LLM), LangChain, and Python to process 250K CVE JSON records. Integrated the Pinecone vector database to store embeddings of CVE data, enabling fast, real-time queries and access to the latest CVE insights.
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Data Processing & Storage: Built a suite of 3 microservices w/ Go for CVE data normalization and Kafka for asynchronous message processing. Ensured seamless data management with Flyway migrations for PostgreSQL, maintaining schema integrity and automating updates.
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Kubernetes Cluster: Deployed a highly available Kubernetes cluster on AWS with multi-AZ deployment. Integrated Istio for secure service-to-service communication, Kafka for real-time messaging, and KMS for encryption, ensuring high availability and scalability for CVE processing and the RAG model. Managed infrastructure with Helm charts and auto-scaling for CVE processing applications, ensuring optimal performance under varying workloads.
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CI/CD Pipelines: Streamlined application deployments by automating AWS AMI image creation using HashiCorp Packer with pre-configured Jenkins and NGINX. Designed robust CI/CD pipelines using Jenkins DSL and Terraform, enabling seamless deployment of applications on Amazon EKS. Integrated GitHub Webhooks for continuous integration, automating Docker image builds and pushes with zero downtime during updates. Adopted Semantic Versioning 2.0.0 and enforced Conventional Commits for automated GitHub Releases, ensuring consistency across deployments. Extended this approach to container image versioning, enabling reliable traceability and rollbacks.
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Service Mesh & Security: Deployed an Istio service mesh with Ingress, VirtualService, and mTLS for secure, reliable communication between microservices. Integrated Kiali and Jaeger for traffic management, tracing, and visualization, reducing troubleshooting time by 30% and improving operational efficiency.
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Centralized Monitoring: Implemented centralized monitoring with the EFK stack and Prometheus/Grafana for logging, metrics collection, and visualization. Achieved 99.9% alert accuracy, reducing mean time to detection (MTTD) by 40%.
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Kubernetes Operator: Designed a custom CRD with Kubebuilder to monitor and process hourly CVE releases, automatically fetching new CVE records and integrating them with Kafka and Pinecone for indexing and real-time processing.
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Security Posture Enhancement: Improved security by automating SSL/TLS certificate management with cert-manager and secret management using SOPS, ensuring zero downtime during key rotations and improving security by 35%.
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LLM Deployment: The Llama-3.1-8b model is deployed using the Ollama service on an AWS GPU instance g5.xlarge, ensuring efficient and scalable LLM deployment and inference.
A cloud-native web application focused on performance and scalability, hosted on Google Cloud Platform:
- Built a robust RESTful API Server following Twelve-Factor App principles, implemented CI/CD with GitHub Actions on Google Cloud, utilizing Cloud SQL and VPC peering for secure database access.
- Developed an event-driven system with Pub/Sub and Cloud Run, enhancing scalability to handle 10x traffic spikes while maintaining response times under 200ms.
- Secured sensitive data with CMEK encryption for Secrets, VM disks, and Cloud SQL, and enforced IAM roles adhering to Principle of Least Privilege (POLP), strengthening overall security.
Northeastern University, Boston, MA | Jan 2025 – May 2025
Accenture, Hyderabad, India | Sept 2021 – Aug 2023
- Certified Kubernetes Administrator (CKA)
- AWS Certified Solutions Architect – Associate
- Microsoft Certified: Azure Fundamentals