AI & Software Engineer
I build reliable software and AI systems across enterprise environments, with experience spanning full stack engineering, cloud deployment, applied AI, and LLM-based workflows.
I am an Engineer with experience building reliable software and AI systems across healthcare, telecom, and enterprise environments. My work spans backend services, full stack applications, cloud deployments, and applied AI, with a focus on practical, secure, and production-ready delivery.
I build full stack applications, APIs, and backend services using Java, Python, React, and cloud-native platforms. My experience includes enterprise systems, microservices, authentication-related work, frontend integration, and production deployment across AWS-based environments.
I work on applied AI systems that connect models, data, and software to solve practical problems in production. My experience includes experimentation, evaluation, deployment, and integration across machine learning and generative AI use cases, with work involving Python services, Amazon Bedrock, and familiarity with agent platforms such as Microsoft Copilot Studio.
I build LLM-driven systems for document understanding, internal knowledge access, and multi-step AI interactions. My experience includes RAG pipelines, agent orchestration, prompt workflows, and grounded response patterns using tools such as LangGraph, LlamaIndex, vector search, and FastAPI.
Designing, Building & Scaling AI & Software Systems
Academic Background & Learning Journey
Master of Science, Data Science
Feb 2024 – Dec 2025
Grade: 3.6/4
Core Skills: Generative AI, Data Science, Advanced Machine Learning, Big Data, Data Mining
Bachelor of Technology, Information Technology
Aug 2016 – May 2020
Core Skills: App Development, Software Lifecycle, Networking, DBMS, Frontend & Backend Systems
Selected credentials across AI, cloud, and software engineering
AWS Certified Solutions Architect Associate
AWS Certified Machine Learning – Specialty
AWS Certified AI Practitioner
Microsoft CoPilot Studio
Career Essentials in Generative AI
AI Agents Course
Certified Kubernetes Application Developer
SAS Viya for Learners Challenge Winner 2024
Microsoft PyTorch Fundamentals
Google Code Jam
Google Kick Start
Techgig Code Gladiators
Core areas across software engineering, generative AI, and production delivery
Supporting production systems on AWS with services and deployment practices used across AI and software workloads.
Building LLM-based solutions including RAG pipelines, agent workflows, grounded response systems, and production-facing AI applications.
Building backend services, APIs, and user-facing applications with attention to maintainability, integration, and dependable delivery.
Supporting build, deployment, and operational workflows with Docker, Kubernetes, Terraform, and CI/CD practices.
Experience across software engineering, applied AI, and cloud delivery
Consistent learning through problem-solving and algorithmic thinking
Coding daily for one full year, showing commitment and discipline.
Recognized in global competitive rankings among LeetCode users.
Mastered a wide range of data structures and algorithms.
Earned elite badges in consistency, contests, and problem milestones.
I recently delivered a live, hands-on session for DevOps Career Hub, architecting and deploying a real-world AI assistant.
This walkthrough covers the full lifecycle: from Python code to scalable cloud infrastructure using AWS Bedrock, Lambda, and API Gateway.
Watch Full WebinarHave a project, question, or just want to chat? I’d love to hear from you!
+61 481 700 945
tayalarajan45@gmail.com