Gopal Bagaswar

Applied AI Engineer | RAG | Agent Systems | Production LLM Applications

I am moving from senior data analytics into applied AI engineering. I build testable systems around retrieval, agent workflows, analytics, and developer automation, with an emphasis on evidence, evaluation, and guardrails.

Selected Projects

Project	Engineering proof	Stack
citipoints	Retail loyalty analytics with ML models and an auditable natural-language-to-SQL layer over synthetic data	TypeScript, Next.js, FastAPI, XGBoost
rag-analytics-assistant	Guardrailed analytics assistant with hybrid retrieval and tool-calling over user-controlled data	Python, FastAPI, DuckDB, RAG
codex-upgrade	Portable Codex CLI skills, prompts, and operating guardrails	Python, Codex CLI
claude-code-toolkit	Hooks and reusable controls for session management and credential protection	JavaScript, Claude Code
officehub	Self-hosted project workspace with timelines and management rollups	TypeScript, Next.js, Postgres, Docker
ai-engineering-receipts	Public interview playbook and evidence index for applied-AI work	Documentation, evidence maps

Verified Open-Source Contributions

Six merged code pull requests, verified against the upstream repositories:

Repository	Contribution
gradio-app/gradio#13396	Convert non-WAV audio output to int16 to prevent playback corruption
gradio-app/gradio#13344	Fix a KeyError involving nested gr.Examples inside gr.render
livekit/agents#5288	Make function-call history preservation configurable in AgentTask
mem0ai/mem0#4461	Add reasoning_effort support for reasoning models
optuna/optuna-integration#278	Fix late binding in BoTorch constraint closures
Mintplex-Labs/anything-llm#5560	Strip Markdown before text-to-speech processing

Engineering Focus

Applied AI : RAG, agent workflows, tool calling, evaluation, guardrails
Backend    : Python, FastAPI, Node.js, PostgreSQL
Frontend   : TypeScript, React, Next.js
Data       : Pandas, SQL, forecasting, segmentation, experimentation
Delivery   : Docker, CI, reproducible validation, evidence-first documentation

Current Direction

• Building public, reviewable AI-engineering proof rather than tutorial clones.
• Contributing tested fixes to the open-source tools used in real projects.
• Looking for applied AI, AI engineering, and AI analytics roles open to remote work from India.

Activity

Daily Build Break

Refreshed every morning by a scheduled workflow in this repository, filtered to safe-for-work posts only. The script is in .github/workflows/daily-meme.yml.

_{realetable — r/ProgrammerHumor · 4,530 upvotes}