AI First Full Stack Engineer (Development and Test) with 9 years of experience building distributed systems, backend microservices, internal UI tools, and end-to-end test automation. Strong in Java, Python, JavaScript, API development, CI/CD, and cloud-native reliability, with a track record of reducing validation cycles from 144 hours to 3 hours. Completed the AI Engineering Cohort with a certificate, adding training in RAG, AI agents, tool calling, MCP, context engineering, LLM evaluation, and safety guardrails to a foundation in software development and quality engineering.
Languages & Runtime: Java, Python, JavaScript, Nodejs
Development: Spring Boot, Dropwizard, Django, Retool, REST APIs, Protobuf
System Design: Microservices, Low-Level Design (LLD), Distributed Systems, API Gateway
Databases & Storage: MySQL, MongoDB, Redis, Aerospike, HBase, Elasticsearch
Cloud & DevOps: AWS, Docker, Kubernetes, CI/CD, Jenkins, Git
Messaging & Observability: Kafka, Prometheus, Grafana, Kibana, Loki
Test Engineering: Playwright, Pytest, TestNG, Cucumber BDD, Appium, Mockito, JMeter; API, integration, end-to-end and performance testing
RAG (Cohort Training): Retrieval-Augmented Generation, embeddings, vector databases, chunking, ingestion, indexing, reranking, query rewriting, HyDE
AI Agents (Cohort Training): Tool calling, ReAct, prompt chaining, orchestration, routing, Model Context Protocol (MCP), context engineering, agent memory, multi-agent systems
AI Evaluation & Safety (Cohort Training): LLM evaluations, LLM-as-a-Judge, hallucination assessment, input/output guardrails, prompt-injection defenses, intent classification
LLM Foundations (Cohort Training): Transformers, tokenization, attention, fine-tuning (LoRA/QLoRA), quantization, multimodal models, agentic system design
AI Engineering Cohort — AI Engg (aiengg.dev), instructor Gaurav Sen | Completed with certificate. Curriculum: LLMs, RAG, AI agents, MCP, context engineering, LLM evaluation, AI safety, and agentic system design.