Shubham Rathod
1.5+
Years of hands-on experience
AI Context Engineer

Shubham Rathod

AI engineer specializing in production-grade intelligent systems at scale. Focus on applied AI — complete systems integrating LLMs, computer vision, automation, and deployment. Turning AI capabilities into reliable, measurable business outcomes.

Profile

Languages
English, Hindi
Education
Integrated MTech, Vellore Institute of Technology, BhopalAI2026CGPA: 7.79.

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Tech Stack

Languages & Runtimes
JavaScriptSQL
Backend & Auth
OAuth 2.0PostgreSQL
Data Engineering
Adaptive Selectors & Fallback LogicCaching StrategiesStructured Extraction PipelinesResilient Ingestion Workflows
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"The true logic of this world is in the calculus of probabilities."

— James Clerk Maxwell

Intelligence Architecture

01

MODEL LAYER

Foundation reasoning & multimodal intelligence powering structured workflows.

GPT-4oClaude 3GeminiLlamaHuggingFace

Used in multi-agent orchestration, structured RAG, and enterprise automation.

02

API & INTEGRATION LAYER

Provider abstraction and multi-model switching via unified interfaces.

OpenAI APIAnthropic APIGemini API
Client → API Gateway → Model Provider
03

DATA & RETRIEVAL LAYER

Contextual grounding using vector search and structured retrieval pipelines.

Adaptive Selectors & Fallback LogicCaching StrategiesStructured Extraction PipelinesResilient Ingestion Workflows
User QueryEmbedVector SearchContext InjectionModel
04

AGENT ORCHESTRATION

Stateful, multi-step reasoning systems with graph-based execution.

LangGraphCustom Agent Systems
PlannerToolsMemoryExecutorOutput
05

BACKEND & SECURITY

Authenticated, access-controlled, production-grade APIs.

OAuth 2.0PostgreSQL
RBACRate LimitingSecure Token Handling
06

PERCEPTION & DEEP LEARNING

Vision pipelines and domain-specific model training.

LangChainMulti-Agent ArchitecturesPrompt EngineeringStructured Output Validation
CNNMultimodal ProcessingEdge Inference
07

DEPLOYMENT & MONITORING

Scalable deployment with logging, monitoring and CI/CD.

Microservices ArchitectureTask Queues & Async PipelinesGit

Latency · Error Rate · Throughput · Cost

08

CLOUD INFRASTRUCTURE

Elastic compute across cloud and serverless environments.

AWSDockerDokploy

Selected Projects

Prism – AI-Powered Recruitment Automation

Prism – AI-Powered Recruitment Automation

Problem

Prism turns the fragmented recruitment process into a cohesive automation layer.

Solution

Built on n8n as the central orchestrator.

Impact

Eliminated 15-30m of manual work per candidate.; Standardized AI scoring criteria for every…

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More projects

Champions Gen: Sports Intelligence Platform

SportsTech

AI-powered player intelligence platform predicting injuries, forecasting performance, and estimating market value for professional sports teams.

Tech
SportsTechPredictive AIMachine LearningPython

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