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Suddapalli Gangadhar

Software Developer at Accelnomics Technologies

Andhra Pradesh

2+ years of work experience

Accelnomics Technologies
Mar 20242 yrs 7 mosPresent

Bengaluru

• Architected an AI Agent Platform that automates Tier-1 technical support workflows, reducing average response time by 50% and freeing the support team to focus on complex escalations. • Built a RAG pipeline on QDrant vector database with hybrid semantic and keyword retrieval, indexing the company knowledge base to deliver grounded, context-aware answers and cut hallucinations. • Designed an LLM evaluation framework covering hallucination, retrieval relevance, and tone, gating each production deploy on regression-test pass rates against a curated test set of real support tickets. • Engineered multi-step agent workflows with LangChain and OpenAI, including tool use, conversation memory, and fallback handling for ambiguous or out-of-scope queries. • Iterated on prompt strategies (few-shot, chain-of-thought, structured JSON output) to lift accuracy on edge-case tickets and standardize agent responses. • Owned full-stack delivery across a polyglot architecture: React.js front end, Node.js + Express.js backend services, and FastAPI (Python) services for AI/LLM workloads, with MongoDB persistence and CI/CD deploys on Azure.
LTIMindtree
Jan 20234 mosApr 2023

India

Suddapalli’s AI Stack

antigravity
antigravity
claude code
claude code
claude
claude
cursor
cursor
langchain
langchain
langgraph
langgraph

Education

Lovely Professional University

Bachelor of Technology - BTech, Computer Science

Lovely Professional University

20194 yrs2023

Intermediate, MPC

Nri junior college

20172 yrs2019

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Headline

Software Developer at Accelnomics Technologies

About

Software Developer at Accelnomics Technologies

Location

Andhra Pradesh

AI stack

antigravity

claude code

claude

cursor

langchain

langgraph

Work experience

Software Developer at Accelnomics Technologies, Mar 2024 - Present · 2 yrs 7 mos, Bengaluru, • Architected an AI Agent Platform that automates Tier-1 technical support workflows, reducing average response time by 50% and freeing the support team to focus on complex escalations. • Built a RAG pipeline on QDrant vector database with hybrid semantic and keyword retrieval, indexing the company knowledge base to deliver grounded, context-aware answers and cut hallucinations. • Designed an LLM evaluation framework covering hallucination, retrieval relevance, and tone, gating each production deploy on regression-test pass rates against a curated test set of real support tickets. • Engineered multi-step agent workflows with LangChain and OpenAI, including tool use, conversation memory, and fallback handling for ambiguous or out-of-scope queries. • Iterated on prompt strategies (few-shot, chain-of-thought, structured JSON output) to lift accuracy on edge-case tickets and standardize agent responses. • Owned full-stack delivery across a polyglot architecture: React.js front end, Node.js + Express.js backend services, and FastAPI (Python) services for AI/LLM workloads, with MongoDB persistence and CI/CD deploys on Azure.

Internship Trainee at LTIMindtree, Jan 2023 - Apr 2023 · 4 mos, India

Education

Bachelor of Technology - BTech, Computer Science, Lovely Professional University

Intermediate, MPC, Nri junior college

Suddapalli Gangadhar - Software Developer in Andhra Pradesh | Tal