Mukesh Durga
Software Engineer building AI-powered systems that scale, recover, and adapt.
NYU CS grad who loves working at the intersection of AI and backend engineering. I design cloud infrastructure and AI workflows that don't break when it matters.
Engineering reliable systems for an AI-native world.
01 — About
Who I am
I'm a software engineer and recent NYU CS grad who likes building systems that hold up under real conditions. Most of my work sits where backend engineering meets applied AI, whether that's distributed services, cloud infrastructure, or LLM workflows that need to stay reliable in production and not just in a demo.
What I enjoy most is taking messy technical problems and turning them into clean, usable systems. Some days that means tracing a production incident back to its root cause, and other days it means wiring an LLM into a workflow that actually has to be dependable. Either way, I care about performance, reliability, and real user impact, and I do my best work when the feedback loop is tight and the ownership is real.
- M.S. in Computer Science, NYU
- New York, NY
- Backend · Cloud · AI · Reliability
02 — Projects
Featured Projects
Systems I've built across AI workflows, observability, analytics, and backend infrastructure.
Natural-Language Analytics
A full-stack app that turns plain-English questions into verified SQL against a connected Postgres or Snowflake database. It runs every query inside a read-only sandbox with timeouts and row limits, then checks that the result actually answers the question before returning it.
- Text-to-SQL
- FastAPI
- PostgreSQL
- Snowflake
- LLMs
03 — Experience
Where I've worked
Backend engineering, AI tooling, and enterprise-scale systems.
Graduate Teaching & Course Assistant
New York University
2024 – 2026
Software engineering, systems, and algorithms.
- Mentor students through backend architecture, API design, authentication, testing, and debugging
- Coach them on data structures, algorithms, complexity tradeoffs, and the edge cases that break solutions
- Review assignments for correctness, maintainability, security, and clean implementation
- Help students turn vague problem statements into practical, reliable technical solutions
Software Engineer
Capgemini
Jul 2023 – Aug 2024
Backend microservices and cloud systems for enterprise platforms.
- Built Java and Spring Boot services powering geospatial and logistics workflows across 8+ backend services
- Cut p99 latency 31% by tuning Redis caching, PostgreSQL queries, and the slowest API paths
- Raised backend throughput 26% with Kafka-based async workflows and gRPC integrations
- Migrated 6 services from EC2-hosted deployments to a self-managed Kubernetes environment
- Reduced recurring regressions 20% with stronger unit tests, CI validation, and monitoring and alerting
Software Engineering Intern
Capgemini
Feb 2023 – Jun 2023
AI-assisted internal tooling and analytics pipelines.
- Built an AI-assisted support assistant that classified incoming requests and routed them through REST workflows
- Cut manual request handling 35% by automating classification, routing, and structured responses
- Built Python and Hadoop ETL pipelines to move advertising operations data into PostgreSQL
- Improved reporting access 27% through cleaner pipelines, schema cleanup, and query optimization
Data Intern
HighRadius
Jan 2022 – Apr 2022
FinTech data workflows, recommendation experiments, and model evaluation.
- Prepared customer and transaction data for a FinTech recommendation workflow
- Built feature-generation steps that turned raw financial data into model-ready datasets
- Compared recommendation model variants using offline metrics and A/B testing analysis
- Supported evaluation that surfaced stronger, more engagement-focused recommendations
04 — Skills
What I work with
The languages, frameworks, and systems I use to build and keep things running.
Languages
- Java
- Python
- TypeScript
- SQL
- C++
Backend
- Spring Boot
- FastAPI
- REST APIs
- gRPC
- WebSockets
- Microservices
- Distributed Systems
- System Design
Frontend
- React
- Next.js
- React Flow
- D3
- Monaco
- Tailwind CSS
AI / ML
- LLM Integration
- RAG
- Embeddings
- Vector Search
- Text-to-SQL
- Multi-Agent Orchestration
- Tool-Calling
- Planning Agents
- Adaptive Model Routing
- LLM & Agent Evaluation
- ML Pipelines
- Online Inference
- Prompt Orchestration
Cloud / DevOps
- AWS
- Docker
- Kubernetes
- GitHub Actions
- Jenkins
- CI/CD
- Git
Data / Infrastructure
- PostgreSQL
- MongoDB
- Redis
- pgvector
- ClickHouse
- Snowflake
- Kafka
- Hadoop
- Spark
- S3/MinIO
Monitoring / Reliability
- Monitoring
- Alerting
- Grafana
- AWS CloudWatch
- Logging
- Tracing
- Root Cause Analysis
- Load Testing
- Regression Testing
05 — Highlights
Quick proof points
HackNYU 2025 Winner
Built SolHive, a blockchain analytics project focused on extracting useful insights from decentralized activity.
Production Monitoring Experience
Real-world infrastructure monitoring, incident investigation, escalation, and reliability workflows.
AWS Certified Cloud Practitioner
Foundational AWS certification covering core cloud services, architecture, security, and pricing — the base I build cloud and infrastructure work on.
Backend + AI Focus
Projects combining backend systems, APIs, databases, AI workflows, and automation.
NYU Graduate Student
Master's student at NYU with academic and project work across software engineering, cloud systems, AI, and infrastructure.
06 — Resume
Want the full version?
Download my resume for a deeper look at my experience, projects, and technical background.