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SP

Shikhar Pandey

Open to work1 years experience

AI Engineer

Hyderabad, INTarget Roles: Backend Engineer • Full-Stack Developer • Frontend Specialist

AI Engineer specializing in production agentic and RAG systems.

GitHub

Standing Rank

Rank Not Available

Developer Badges

No badges earned yet

Skills & Technologies

17 skills
langchainlanggraphrag pipelinespineconellmsllmopsfastapipythontensorflowpytorchawsgcpdockersqlmongodbreact.jstypescript

Work Experience

AI Engineer (Trainee Engineer)

KLOUDGIN SAAS PVT LTD

Mar 2025 - Present Hyderabad, IN
  • Architect a custom framework to execute agentic workflows, enabling advanced reasoning pipelines with dynamic tool-calling, memory persistence, and conditional branching; develop end-to-end RAG conversational AI solutions seamlessly integrating Pinecone vector databases and LLM APIs for real-time inference.
  • Architected and deployed an intelligent ticket assistance agent analyzing historical records and enterprise sources, accelerating mean time to resolution (MTTR) by up to 2x.
  • Engineered automated ETL pipelines (FastAPI, AWS/GCP: Bedrock, EC2, Lambda, S3, SageMaker) to ingest and quantize unstructured data into a self-hosted, S3-backed vector store, cutting memory footprint and search latency by approximately 200ms.
  • Built a RAGAS-evaluated chat assistant automating FAQ/policy responses and predictive ML model for location-based risk assessment, reducing risk of digging in a specified location.
  • Processed 500,000 documents for multiple entities, adapting vector dimensions; built AI automation tools using RAG pipelines to generate structured documentation and HTML reports from enterprise sources, reducing manual reporting time by 80%.

Projects

Autocode - Multi-Agent TDD System

LangGraphPythonDockerGemini
  • Architected an autonomous coding ecosystem featuring 5 specialized agents collaborating via a LangGraph supervisor to generate Python features end-to-end; championed TDD by deploying a specialized Tester agent to write comprehensive pytest cases executing validation in a sandboxed Docker container with self-healing retries.

Road Extraction Using FCN

PythonTensorFlowKerasscikit-learn
  • Trained a Fully Convolutional Network (FCN) on satellite imagery for automated road network extraction, managing the end-to-end data preprocessing, model training, and inference pipeline.
  • Evaluated performance using IoU and pixel accuracy; applied data augmentation to minimize overfitting, and built an OpenCV/NumPy preprocessing pipeline for high-res imagery.

ExploreIt - Full-Stack Social Places App

MERN StackReactNode.jsMongoDB
  • Developed a robust full-stack social application featuring JWT authentication, RESTful APIs, and geolocation services to facilitate the seamless sharing of location-based content and media.
  • Integrated geolocation APIs with MongoDB aggregation pipelines for spatial querying, and optimized state management via Redux for responsive media handling.

Leaderboard Standings

Leaderboard Position Pending

Global test scores, peer standing percentiles, and algorithm leaderboard ranks are updated dynamically.

Assessment Highlights

Assessments Not Completed

Coding evaluations, system assessment results, and conceptual score badges will appear here after taking a test.

AI Collaboration Score

AI Collaboration Score Pending

Developer coding behavior, assistant cooperation, and AI pair-programming indicators are evaluated during live coding sessions.

Role Compatibility Profile

Role Compatibility Analysis Pending

Custom matching reports, candidate role compatibility percentiles, and core engineer strength profiles are processed once conceptual code screenings are complete.

Achievements

Document Processing Efficiency

Processed 500,000 documents for multiple entities, reducing manual reporting time by 80%.

MTTR Improvement

Accelerated mean time to resolution (MTTR) by up to 2x for intelligent ticket assistance agent.

ETL Pipeline Optimization

Cut memory footprint and search latency by approximately 200ms for ETL pipelines.

About Details

Professional Bio

AI Engineer who has shipped production agentic and RAG systems. Experienced in multi-agent LangGraph pipelines, Pinecone-backed retrieval, and LLMOps deployments on AWS/GCP. Comfortable owning a system end-to-end, from architecture through FastAPI deployment and RAGAS-based evaluation.

B.Tech. Computer Science & Engineering

VIT University, Chennai (2021 - 2025)

Class 12th & 10th (CBSE)

St. Joseph’s Co-Ed, Bhopal ( - 2021)

Languages: English, Hindi