Senior AI and Data Engineer with 10+ years of experience building and operating production-grade AI, data, and cloud-native systems. Specialized in Generative AI, NLP, retrieval-augmented generation (RAG), and large-scale data pipelines. Extensive experience deploying LLM-powered applications using LangChain, OpenAI, Azure OpenAI, and AWS Bedrock. Strong background in Python, cloud platforms, Kubernetes, DevOps automation, and microservices. Proven ability to deliver secure, scalable AI solutions and collaborate with executives, clients, and cross-functional teams.
Deployed decentralized Vector.dev instances using Kubernetes for ingesting, transforming, and routing logs and metrics to systems including Azure, AWS, GCP, and Splunk. Transformed logs using VRL to schemas such as OCSF for security data using Python, Bash, and Perl. Used Git and GitHub Actions to deploy declarative jobs and pipelines across cloud providers. Built interactive dashboards and alerting workflows with OpsGenie.
Led design and deployment of enterprise-scale GenAI solutions across AWS and Azure. Built LLM-powered applications using Azure OpenAI and LangChain for RAG, agents, memory, routing, guardrails, content moderation, and sentiment analysis. Designed prompt lifecycle management systems and engineered RAG systems with MongoDB and Elasticsearch. Deployed AI microservices and APIs using Python and TypeScript. Built data ingestion, cleansing, and observability pipelines using ELK, MongoDB, and NiFi.
Architected and deployed AWS-based data ingestion, cleansing, and transformation pipelines using ELK, Ansible, and Python. Enabled self-service analytics dashboards and visualizations using Elasticsearch and Grafana. Orchestrated infrastructure using Terraform and CI/CD pipelines via GitLab.
Built distributed cloud systems with CI/CD automation using Docker, GitLab, and Ansible. Implemented services including Apache Kafka, Redis, and Elasticsearch. Coordinated with stakeholders on scope, requirements, and timelines. Applied Agile methodologies to improve delivery speed. Authored Python scripts reducing staging times from days to under five minutes. Led development of Spring Boot microservices and built predictive analytics and monitoring solutions using Python and Django.
Founded and led the Automation Solutions department. Developed ETL processes using Python and secure FTP/SFTP transfers. Designed automated compliance error reporting systems using Java. Improved data accuracy and reduced manual errors through automation. Managed daily IT operations and provided technical support for business-critical systems.
Bachelor of Science, Computer Science and Minor in Mathematics
Master of Science, Data Analytics Data Science
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