Markandey Singh — Director of Engineering, Bangalore India

Markandey Singh is a Director of Engineering at MoneyView, one of India's top fintech companies. With over 10 years of experience building distributed systems, AI agent pipelines, and large-scale engineering teams, Markandey has progressed from individual contributor to director at MoneyView.

AI Agents and MCP Orchestration

Markandey builds AI agent systems using the Model Context Protocol (MCP). His MCP Agent Farm orchestrates multiple AI agents with different LLM providers — Claude, GPT-4, and local Qwen models via Ollama — routing queries intelligently to minimize cost. The system routes 93% of queries to free local models, achieving 76% cost savings compared to cloud-only AI.

Engineering Career Journey

Career path: NTPC (power grid systems, C++, SCADA) → SAP Labs (enterprise software, Java) → Opinio (startup, first product scale) → CureFit/cult.fit (health-tech backend, millions of users) → MoneyView (fintech platform, IC to Director of Engineering over 7+ years).

Technical Expertise

Distributed systems, Kafka, Kubernetes, AWS, Node.js, Java, AI query routing, retrieval-augmented generation (RAG), local LLMs, Ollama, engineering leadership, platform engineering, fintech infrastructure.

Location

Based in Bangalore, Karnataka, India.

B.Tech Electronics & Communication, VIT Vellore, 2014.

markandey.in
0101THE FOUNDATION

Where I learned how large systems work

Started at NTPC, where India's power grid runs on legacy systems that cannot afford to fail. Moved to SAP Labs, building enterprise software at global scale. This is where I developed an obsession with reliability, uptime, and systems that serve millions without anyone noticing.

NTPC

Development Specialist

Power grid systems. Zero margin for error.

C++SCADAEmbedded

SAP Labs

Developer

Enterprise platforms serving Fortune 500.

JavaABAPEnterprise

Opinio

Developer

First startup. First taste of building from zero.

Full-stackNode.js
0202THE STARTUP ENGINE

Where I learned to build fast and ship fearlessly

CureFit (now cult.fit) was a rocket ship. Backend systems for a health-tech platform scaling to millions of users across fitness, food, and mental wellness. This is where I learned that speed and quality aren't opposites — they're both functions of good architecture.

CureFit

Lead Developer

Designed and built backend systems from the ground up.

JavaMicroservicesAWSKafka
0303THE SCALE MACHINE

Building the platform that powers India's lending

MoneyView is a top-10 Indian fintech. I've grown from IC to Director of Engineering, now leading Operations, Platform, and DevOps. Our systems process millions of loan applications, handle financial data with zero tolerance for errors, and serve users across India.

MoneyView

Platform Engineering

Scalability, availability, and cost-efficiency at fintech scale.

AWSDynamoDBRedshift

MoneyView

DevOps & SRE

CI/CD pipelines, monitoring, incident response for financial systems.

DockerK8sTerraform

MoneyView

Engineering Leadership

Grew from IC → Lead → Manager → Senior Manager → Director.

Team BuildingStrategyHiring

7+

Years at MoneyView

IC → Director

Growth

Millions

Users served

0404THE AI LAYER

Where systems learn to think

AI isn't a buzzword in my world — it's running in production. I've built intelligent query routing systems that classify user intent and route to the right model (93% to free local models, 7% to paid APIs — saving 76% on costs). I run an MCP Agent Farm for orchestrating AI tools, a RAG pipeline with vector search, and I believe the future of engineering leadership includes knowing how to architect AI-native systems.

Personal

AI Query Routing

Smart classification: 93% local, 7% cloud. 76% cost savings.

QwenClaudeNLP

Personal

MCP Agent Farm

Orchestration layer for AI agents with tool access.

MCPAgentsOrchestration

Personal

RAG + Knowledge Store

Vector search over curated knowledge. Semantic retrieval.

pgvectorEmbeddingsOllama

Let's build something together

I'm always interested in conversations about engineering leadership, AI systems, and ambitious technical challenges.