Hi, I'm Akash
AI & Full-Stack Developer
I build production LLM systems and full-stack apps at the intersection of AI and code. ✨
About Me
I'm Akash, a Software Developer with 2+ years of experience in Generative AI, RAG, and full-stack development, building production LLM systems with LangChain, LangGraph, and Azure OpenAI.
I've delivered measurable impact — ~4× developer productivity gains, 50% efficiency improvements, and onboarding timelines cut from 12+ months to under 6 — by shipping agentic AI services, MCP-based microservices, and RAG pipelines that put LLMs to work on real problems.
- 🤖 Generative AI & Agents (LangChain, LangGraph, RAG, MCP)
- 🧠 ML / Deep Learning & NLP (PyTorch, TensorFlow)
- 💻 Full-stack Development (React, Next.js, FastAPI, .NET)
- ☁️ Azure AI, Docker & cloud-native architectures
- ⚡ Production LLM systems with measurable business impact
Projects
Tech Stack
Languages
Artificial Intelligence
Full Stack Development
Cloud & DevOps
Experience
Software Developer
Octave (formerly Hexagon) — Hyderabad, India
May 2024 – Present
- Built a secure MCP-based microservice for OData-driven data access, integrating Okta authentication and Azure OpenAI to enable LLM-powered configuration of the InConcert application — reducing customer onboarding from 12+ months to under 6months.
- Led org-wide AI-assisted development by standardizing GitHub Copilot workflows with custom plugin integrations and mentoring a team of 7 engineers, achieving ~4× productivity gains.
- Built a Retrieval-Augmented Generation (RAG) pipeline with LangChain and FAISS for document ingestion, embeddings-based semantic search, and LLM-powered retrieval, cutting documentation-lookup time by 50%.
Software Developer Intern
Hexagon — Hyderabad, India
Aug 2023 – May 2024
- Improved frontend performance and maintainability via TypeScript migration, rendering optimization, and design-system consolidation — boosting frame rate from 30–45 fps to 60 fps.
- Reduced developer styling effort by 40% through adoption of the organization's pre-built component library.
- Accelerated stakeholder feedback cycles from 45 days to 7 days by introducing Storybook-powered component showcases for reviews and client demos.
🎓 Education
2024
B.Tech in Computer Science Engineering (AI & ML)
B V Raju Institute of Technology
Specialized in Artificial Intelligence and Machine Learning
2020
Higher Secondary School
Narayana Junior College
Majored in Physics, Chemistry and Mathematics.
2018
Secondary School Certificate (SSC)
St. Arnolds High School
Completed with a focus on Science and Mathematics.