Yendluri Pavan Ram Chandar

DevOps Engineer

Vijayawada, Andhra Pradesh, India1 yr 7 mos experience
AI EnabledAI ML Practitioner

Key Highlights

  • Designed production-grade Agentic AI systems.
  • Boosted query accuracy by 25% in Document QA.
  • Automated 60% of customer support inquiries.
Stackforce AI infers this person is a Data Engineering and AI specialist focused on enterprise-level solutions.

Contact

LinkedIn

Skills

Core Skills

Agentic AiLlm OrchestrationEtl Pipeline OptimizationGenerative Ai SolutionsAi-powered Fraud DetectionDocument Qa SystemAi Customer Support

Other Skills

AgnoModel Context Protocol (MCP)Apache SparkdatabricksGenerative AILLMsAnsibleProject ManagementMLPythonScikit-learnLangChainLlamaIndexChromaDBLLM

About

I build AI systems that don't just answer questions — they think, plan, and act autonomously. Currently working as an Agentic AI Engineer at Genpact, I design and deploy production-grade Multi-Agent Systems, RAG pipelines, and LLM-powered applications that eliminate manual bottlenecks and drive measurable business outcomes. My work spans the full GenAI stack — from data engineering on Databricks to orchestrating autonomous agents with Agno, LangChain, and Model Context Protocol (MCP). What I've shipped: → Document QA system (RAG + LangChain + ChromaDB) → boosted query accuracy by 25% → Financial fraud detection platform (ML + Python) → reduced false positives by 15% → ETL pipeline optimization on YODA project (Apache Spark + Databricks) → 30% faster processing → Autonomous Multi-Agent SDLC system (AutoGen + LangChain) → cut manual dev intervention by 50% → AI customer support agent → automated 60% of routine support inquiries My stack: LLMs (GPT-4, Llama 3, Gemini) · LangChain · LlamaIndex · Agno · RAG · Vector DBs (ChromaDB, FAISS) · Apache Spark · Databricks · Python · FastAPI · Docker · Kubernetes · AWS · Azure Certifications: Databricks Certified Data Engineer Professional & Associate I'm passionate about pushing the boundaries of what Agentic AI can do in enterprise environments — building systems where LLMs don't just generate text, but autonomously complete complex, multi-step workflows. Open to connecting with AI engineers, researchers, and teams building the next generation of intelligent systems

Experience

1 yr 7 mos
Total Experience
1 yr 7 mos
Average Tenure
1 yr 7 mos
Current Experience

Genpact

3 roles

Agentic AI Engineer

Mar 2026 – Present · 2 mos · On-site

  • Architecting production-grade Agentic AI systems using Agno framework and
  • Model Context Protocol (MCP), enabling autonomous multi-step task execution
  • across enterprise workflows.
  • Designing and deploying LLM orchestration pipelines with tool-use, memory,
  • and planning capabilities, reducing manual engineering intervention by 40%+.
  • Integrating MCP servers with internal enterprise APIs to create context-aware
  • AI agents capable of real-time decision-making and action execution.
  • Collaborating with cross-functional teams to translate business requirements
  • into scalable Agentic AI architectures aligned with production SLAs.
AgnoModel Context Protocol (MCP)Agentic AILLM orchestration

Data Engineer - Gen AI

Oct 2024 – Mar 2026 · 1 yr 5 mos · On-site

  • Built and optimized large-scale ETL pipelines using Apache Spark and
  • Databricks, processing millions of records with 30% improvement in throughput.
  • Developed and deployed Generative AI solutions integrating LLMs with
  • enterprise data pipelines, enabling intelligent document processing and
  • automated insights generation.
  • Engineered RAG (Retrieval-Augmented Generation) pipelines using LangChain
  • and LlamaIndex, improving information retrieval accuracy by 25% for internal
  • knowledge systems.
  • Implemented real-time monitoring and observability for ML pipelines using
  • Prometheus and Grafana, reducing incident response time by 35%.
  • Achieved Databricks Certified Data Engineer Professional certification
  • (Oct 2025) while delivering production AI systems at scale.
Apache SparkdatabricksETL pipeline optimizationGenerative AI solutions

One Data & Gen AI Intern

Feb 2024 – Sep 2024 · 7 mos · On-site

  • Engineered ETL pipeline optimization for the YODA project using Apache Spark
  • and Databricks, boosting data processing efficiency by 30% and reducing
  • batch runtime significantly.
  • Built an AI-powered financial fraud detection platform using ML classification
  • models (Python, Scikit-learn), reducing false positive rates by 15% and
  • saving analyst review hours.
  • Developed a multimodal Document QA system using LangChain + LlamaIndex +
  • ChromaDB, integrating text and image understanding to improve query response
  • accuracy by 25%.
  • Deployed an AI customer support agent using LLM + LangChain tool-use,
  • automating 60% of routine Tier-1 support inquiries with sub-3s response time.
  • Completed Genpact's intensive Skydive program covering advanced data
  • engineering, ML systems, and GenAI application development.
AnsibleProject ManagementAI-powered fraud detectionDocument QA system

Verzeo

Verzeo Campus Ambassador

Feb 2022 – Apr 2022 · 2 mos · Remote · Remote

  • Grew Verzeo's student community by engaging 200+ peers through tech workshops
  • and webinars focused on ML and data science fundamentals.

Education

Lovely Professional University

Bachelor of Technology (B.Tech) — Computer Science and Engineering (Honors) with a Specialization in Data Science

Aug 2020 – Jul 2024

Sri Chaitanya Junior College

Intermediate (Class XII)

Jun 2018 – Apr 2020

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