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MAHADEV MANERIKARAI ENGINEER PORTFOLIO
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Mahadev Manerikar

AI Engineer  |  Backend-focused developer

Hi, I’mMahadev
Manerikar

I build production-grade AI systems, multi-agent platforms, and scalable backend APIs on Azure.

Pune, India · Open to opportunities

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...Building since Mar 2024
2K+Documents ingested
60%Latency reduction · 15s to 6s
AzureProduction cloud

Featured work

Content Discovery Workflow

Production content discovery workflow for an agentic recommendation platform, with optimized response time and measured search quality.

LangChainAzure AI SearchCosmos DB
15s → 6s response time

Continuum Control Plane

Multi-agent ServiceNow incident automation connecting support teams with Splunk signals and specialist agents.

LangGraphMCPWebSockets
Orchestrated incident workflows

DocVision-RAG

Multimodal retrieval for diagrams and screenshots, returning grounded answers with source pages and images.

Multimodal RAGVisionSSE
Searchable visual knowledge

Agent Orchestration Platform

Multi-user platform where database configurations become shareable, live agents and teams without redeployment.

AgnoFastAPISSE
Agents configured as data
// toolbox

Technical stack

The tools I use to design, build, evaluate, and operate production AI and backend systems.

AI & Agent Systems

LLMsAgentic & Multi-Agent SystemsLangGraphLangChainMCPMicrosoft Agent FrameworkAgnoAzure AI FoundryPrompt EngineeringGuardrails

Retrieval & Evaluation

RAGEmbeddings & Vector SearchAzure AI SearchPGVectorLLM-as-a-JudgeAzure AI Evaluation SDKRelevance & Groundedness

Backend & Data

PythonFastAPIREST APIsNode.jsReactWebSocketsSSESQLAlchemyPostgreSQLSQL ServerCosmos DB

Azure & DevOps

Azure Container AppsAzure FunctionsLogic AppsApp ServiceAPIMKey VaultManaged IdentityMSALBlob StorageDockerAzure DevOps CI/CD

Observability

OpenTelemetryAzure Application InsightsAzure MonitorSplunkCost & Latency Tracing

Languages

PythonJavaScriptTypeScriptSQL
// experience

Experience

Equations Work · Pune, India

AI and software engineering, from early prototypes to production systems.

AI Engineer

Equations Work · Pune

OCT 2024 — PRESENT

Build production multi-agent and RAG systems on Azure. Focus on orchestration, search quality, evaluation, observability, and performance—reducing a workflow response from 15 seconds to 6 seconds and search hallucinations from 8.2% to 2.2%.

  • Moved the AVS Content Discovery Workflow from hosted agents to merged LangChain agents, reducing response time from 15 seconds to 6 seconds.
  • Built agent evaluation and hallucination measurement; reduced the search tool hallucination rate from 8.2% to 2.2%.
  • Designed specialist-agent orchestration for incident analysis, ServiceNow automation, and live chat streaming.
  • Resolved production API timeouts at million-record scale with cursor-based pagination.
LangGraphAzure AI FoundryFastAPIMCPAzure AI Search

Trainee Software Engineer

Equations Work · Pune

MAR 2024 — OCT 2024

Built Azure AI Foundry agents and Logic Apps integrations, and delivered proof-of-concept work for sales coaching and real-time vehicle tracking.

  • Built three Azure AI Foundry agents for a sales coaching proof of concept.
  • Connected Dynamics 365 and SQL Server workflows using Azure Logic Apps.
  • Developed a real-time vehicle monitoring proof of concept with live tracking and PostgreSQL zone-duration logic.
PythonAzure AI FoundryLogic AppsPostgreSQL

Want more detail on the systems I’ve delivered at Equations Work?

// professional-projects

Equations Work projects

Selected AI and software projects delivered as part of my professional experience.

Content Discovery Workflow

Production agent workflow for personalized content recommendations.

  • Moved from hosted agents to a merged LangChain architecture, reducing response time from 15 seconds to 6 seconds.
  • Built agent evaluation and hallucination measurement, reducing the search tool hallucination rate from 8.2% to 2.2%.
  • Added semantic search, language-based index selection, conversation state, and per-agent cost tracking.
LangChainAzure AI SearchCosmos DBApplication Insights

Incident Automation Platform

Coordinated agents that help support engineers investigate and resolve cloud incidents.

  • Built specialist workflows for log analysis, incident similarity, root cause analysis, severity scoring, and ticket updates.
  • Connected ServiceNow workflows through MCP services with streaming chat and operational observability.
LangGraphMCPFastAPIWebSocketsAzure

Enterprise Knowledge Assistant

Hybrid retrieval assistant for enterprise documents, with automated index ingestion.

  • Combined vector and keyword retrieval across more than 1,000 documents to improve relevance and reduce hallucinations.
  • Automated document ingestion and index updates with cloud functions and blob storage.
RAGAzure AI SearchAzure FunctionsBlob Storage

Property Intelligence Platform

AI-assisted property and investor research with automated reporting.

  • Built data extraction, ETL, and ranking pipelines for financial and property insights.
  • Automated investor-ready reports, saving more than eight hours of manual work per week.
Agentic AIETLDockerAzure DevOps

Sales Coaching Assistant

A proof of concept using specialized agents to support sales coaching workflows.

  • Created orchestration, sentiment analysis, and email assistant agents.
  • Connected Dynamics 365 and SQL Server data with workflow automation.
Azure AI FoundryLogic AppsDynamics 365

Real-Time Vehicle Tracking

Live vehicle monitoring dashboard with event-driven updates and notifications.

  • Implemented live tracking, automated email notifications, and an event-refreshing dashboard.
  • Added a PostgreSQL procedure to calculate time spent in each zone.
PostgreSQLReal-timeDashboard
// independent-work

Personal projects

Independent builds and experiments. Open a repository to explore the code.

GitHub link preview for the agno-agents-hub repository

agno-agents-hub

Agent Orchestration Platform

A multi-user platform where agent and team configurations live in a database and become runnable at request time, without redeploying.

  • Users configure agent roles, instructions, tools, and model settings, then compose teams with a coordinator and ordered members.
  • Runs execute outside the HTTP request and stream output over SSE; status, token usage, duration, and ownership are tracked.
AgnoFastAPISSEMulti-user
View repository
GitHub link preview for the docvision-rag repository

DocVision-RAG

Multimodal document search

A RAG platform that makes PDF diagrams, flowcharts, and screenshots searchable alongside document text.

  • Converts PDFs to Markdown, analyzes extracted images with a vision model, and places image analysis back in its original context.
  • Uses header-aware chunking and cosine vector search to return cited pages and source images.
PythonVision modelsRAGAsync ingestion
View repository
GitHub link preview for the ServiceNow MCP repository

ServiceNow MCP Server

Agent-ready ticket workflows

An MCP server that gives AI assistants tools to retrieve and update ServiceNow incidents, with both stdio and SSE transports.

  • Provides incident lookup and update tools through local stdio integration or an HTTP-based SSE server.
MCPServiceNowSSEPython
View repository
GitHub link preview for the Ingress AI repository

Ingress AI

Unified LLM gateway

An OpenAI-compatible gateway that routes requests across LLM providers through one API, without changing client code.

  • Routes models across providers with retries and automatic failover, plus caching and rate limits.
  • Uses virtual keys and records token usage and costs in a shared ledger.
LLM GatewayOpenAI-compatible APIRoutingCost tracking
View repository
// education-and-recognition

Education, awards & certifications

The foundations behind the systems I build today.

B.E. Computer Engineering

Zeal College of Engineering and Research, Pune · 2020–2024 · CGPA 8.90/10

Higher Secondary Certificate

SVM & Jr College of Science, Kudase, Sindhudurg · 2018–2020 · 77.23%

Unstoppable Contributor Award · 2025–26

Equations Work · Recognized for contributions to a production agentic AI project, including latency reduction, evaluation, and production defect resolution.

Certifications

Anthropic — Introduction to Model Context Protocol
DeepLearning.AI — LangChain for LLM Application Development (2024)

// contact

Let’s build something that ships.

Open to AI engineering and backend opportunities. Send a note or connect through one of the links.

mahadev@portfolio:~$ help
Available: help, clear, /projects, /personal, /experience, /skills, /education, /contact, /home
:~$