Rishabh Jain
I’m Rishabh Jain, an AI & backend engineer with 5+ years of experience building scalable systems in Python and Golang, especially for production AI assistant products.
About
I’m Rishabh Jain, an AI & backend engineer with 5+ years of experience building scalable systems in Python and Golang, especially for production AI assistant products. I work on multi-agent orchestration, LLM integration, RAG pipelines, vector search, and practical long-term memory using Redis and vector databases to make assistant behavior more context-aware and personalized.
In my recent roles at Pansophic Technologies (AIlyra.ai), I’ve built and integrated multiple core agents and subagents with tool ecosystems (email, calendar scheduling, information retrieval, and knowledge assistance), improved latency by parallelizing workflows, and reduced token costs by modular prompt structuring. I also enjoy building reliable backend services (including Golang performance tuning with pprof) and shipping secure, sandboxed AI-driven features—right up to integrating messaging experiences like WhatsApp and creating automated presentation decks.
- 6 years' experience
- Joined October 2026
Industry experience
- Software & Internet
- Gaming
- Professional Services
- Computers & Electronics
Work experience· 6 roles
Built and integrated multi-agent orchestration with 3 core agents, 10 subagents, and 15+ tools for email, calendar scheduling, real-time retrieval, and knowledge assistance. Implemented intent-driven workflows with ADK-based agent state management, modular prompt design to reduce token usage, and long-term memory using Redis plus retrieval/vector mechanisms for personalization. Improved performance by parallelizing sequential agent execution, built a sandboxed environment for secure AI file generation, and integrated WhatsApp messaging into the assistant platform. Engineered an AI Presentation Agent to generate structured PowerPoint decks with automated visual storytelling (estimated 80% time reduction for manual deck creation). Set up CI/CD pipelines using GitHub Actions and deployed on AWS EC2; contributed to frontend features using React with AI-assisted development tools.
Built and integrated a multi-agent orchestration system for Allyra, including 3 core agents, 10 subagents, and 15+ tools spanning email, calendar scheduling, real-time information retrieval, and knowledge assistance. Implemented intent-driven workflows with ADK-based agent state management for context-aware behavior. Reduced LLM token consumption by refactoring prompts into static/dynamic segments and modular persona/skills, lowering per-request inference cost. Added long-term memory and contextual reasoning using Redis, vector databases, and retrieval-based mechanisms to improve personalization and accuracy. Parallelized sequential agent execution to reduce end-to-end latency, and implemented a sandboxed environment for secure AI-driven file generation. Integrated WhatsApp into the assistant platform and engineered an AI Presentation Agent that generates structured PowerPoint decks with automated visual storytelling. Set up CI/CD with GitHub Actions and deployed services on AWS EC2; c
Developed scalable REST APIs in Golang for gaming and sports analytics platforms, addressing performance and security for real-time experiences. Led backend development of a Ten-Pin Bowling scoring engine including gameplay logic and automated calculations. Built APIs for Live Fantasy Stats across major US leagues (player/team stats, matchups, injuries, scoreboards). Profiled services with pprof and optimized CPU usage for real-time workloads.
Education
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