Headline

Full-Stack Al/ML Engineer | GenAI LLMs MLOps Cloud DevOps Cybersecurity | 20+ ProductionSystems with 25-40% Efficiency Gains & 3x Scalability

About

Technology professional with hands-on experience delivering end-to-end systems across AI/ML, Generative AI, software engineering, cloud infrastructure, DevOps, MLOps, cybersecurity, and data platforms. • Built and deployed 12+ AI/ML and GenAI solutions—including LLM-powered chatbots, NLP pipelines, and recommendation engines—improving automation and decision-making efficiency by 25–40% • Developed 15+ full-stack applications and APIs, supporting 10K+ users with 99.9% uptime • Designed and optimized cloud-native architectures (AWS/GCP/Azure), reducing infrastructure costs by 20–30% while enabling 3× scalability • Implemented CI/CD pipelines and DevOps automation, reducing deployment time by 50–70% • Applied MLOps practices (model versioning, monitoring, retraining), improving model performance by 15–25% and minimizing production issues • Deployed and managed production ML models using automated CI/CD workflows for continuous integration, testing, and delivery • Applied security-first practices, identifying and mitigating 40+ vulnerabilities, strengthening system reliability and compliance • Engineered data pipelines handling 2–5 TB of structured and unstructured data, enabling analytics and ML workflows • Strong Python programming skills with hands-on experience using TensorFlow, PyTorch, and Hugging Face for building, training, fine-tuning, and deploying ML and LLM-based models • Proficient in SQL, working extensively with structured and unstructured datasets for analytics, feature engineering, and machine learning pipelines • Hands-on experience with AWS services, including SageMaker for ML model training and deployment, EC2, S3, and Lambda for scalable cloud-based workflows • Experience containerizing applications and ML workloads using Docker, and orchestrating cloud-based infrastructure with Kubernetes • Applied computer vision techniques as part of intelligent systems and ML-driven decision-support applications Technical Domains AI • ML • GenAI • LLMs • NLP • Computer Vision • Software Engineering • Full-Stack • Cloud • AWS • DevOps • CI/CD • MLOps • Docker • Kubernetes • Cybersecurity • Data Engineering • SQL • Python • Automation • APIs I focus on delivering measurable outcomes—performance gains, cost efficiency, reliability, and security—while collaborating with cross-functional teams to take solutions from concept to production. 📌 Open to opportunities in AI/ML, Software Engineering, Cloud, DevOps, MLOps, and Cybersecurity 📌 Interested in high-impact roles, modern tech stacks, and growth-focused teams

Location

United States

AI stack

codex

opencode

claudecode

Work experience

Technical Architect at Salesforce, Jul 2026 - Present · 2 mos, California, United States

Technical Architect - Vendor at Norfolk Southern, Jul 2026 - Present · 2 mos, United States

Technical Architect at Cognizant, Jun 2026 - Present · 3 mos, United States

Technical Lead at Cognizant, May 2026 - Present · 4 mos, Hybrid

Technical Lead - Vendor at UPS Supply Chain Solutions, Apr 2026 - Present · 5 mos

Agentic AI Architect at Cognizant, Apr 2026 - May 2026 · 2 mos, Hybrid

Graduate Research And Teaching Assistant at University of North Carolina at Charlotte, Jan 2026 - Apr 2026 · 4 mos, Charlotte, North Carolina, United States

Education

Master's degree, Computer Science, University of North Carolina at Charlotte

Post Graduate Diploma, Artificial Intelligence & Machine Learning, Indian Institute of Technology, Madras