BALARAJBALARAJBALARAJBALARAJ
FULL-STACK
& AI / ML
ENGINEER
Architecting scalable event-driven infrastructure and robust multi-agent systems.
CSE · AI & ML
About Me
Building AI That
Ships to Production
Focused on building real-world AI systems — not just models, but deployable products.
I'm a 1st-year B.Tech CSE student at PES University specializing in AI & ML. I build and deploy production-grade AI systems, including CareerLens (40,000+ LOC, 32 services) and AgriSence (GCP-based ML platform with 400+ commits).
I'm a National-level hackathon winner with ₹2.75L+ in prizes—most notably securing a flagship victory in the Google GenAI Hackathon. I hold 35+ top-tier certifications across multi-cloud infrastructure and cybersecurity, and actively shape open-source ecosystems with merged contributions to Ubuntu, Pandas, and NumPy (GitHub Pull Shark ×2).
Capabilities
Skills & Capabilities
I design, build, and deploy production-grade AI systems — from model development to scalable cloud infrastructure.
AI Systems Engineering
- Design and build LLM-powered applications using RAG, tool-calling, and multi-agent workflows
- Deploy models using Vertex AI / Gemini APIs with real-time inference pipelines
- Optimize for latency, cost, and scalability in production environments
Full-Stack AI Development
- Build end-to-end AI products with seamless frontend–backend integration
- Develop scalable APIs for ML services and real-time applications
- Focus on clean architecture, modular design, and performance
Cloud & MLOps
- Deploy and manage applications on GCP (Cloud Run, Firestore, Functions)
- Containerize services using Docker and design microservice architectures
- Handle CI/CD, monitoring, and production reliability
Security & Reliability
- Implement secure architectures for AI systems and APIs
- Work with encryption, network analysis, and system-level debugging
- Design systems with resilience and fault tolerance in mind
Production ExperienceHighly Unique
Where I've Applied These Skills:
CareerLens32 Microservices
Built scalable AI-powered backend (40K+ LOC) processing real-time generation queues and embedding pipelines.
AgriSenceGCP Deployed
Deployed end-to-end ML architectures handling image segmentation models on scalable cloud functions.
Complete Arsenal
Engineering Portfolio
I design and deploy complex
AI systems at scale
Here's proof that I build real-world systems with impact, performance, and architecture in mind.
VaidyaOS
Advanced AI healthcare platform for intelligent, real-time, multilingual medical assistance using on-device edge AI and offline capabilities via lightweight GGUF models.
Offline-first architecture with Edge AI inference & Llama.cpp
CareerLens
Built an AI-powered career platform that analyzes resumes, identifies skill gaps, and generates personalized career paths. Designed as a microservices system and deployed for real-world usage.
Event-driven microservices architecture with parallel embedding queues
AgriSence
Developed a real-time AI farming system for crop disease detection and advisory. Integrated ML models with satellite data and multilingual support, deployed on GCP for scalable access.
Serverless ML inference pipeline with real-time edge sync
OmniSence
Engineered a multimodal creative storytelling engine processing text to audio and video. Combined LLMs, Imagen, and Cloud TTS for real-time narrative generation.
Real-time streaming pipeline with async media generation
TaskForze
Created a multi-agent productivity system that coordinates 5 specialized AI sub-agents to manage workflows, with automated escalation via WhatsApp and AI voice calls for missed deadlines.
Multi-agent orchestration system with vector retrieval
HealthMesh v2.0
Built a HIPAA-ready clinical AI platform combining 6 specialized healthcare agents with a prescription bridge API to link clinical insights to hyperlocal medicine delivery.
FHIR R4 compliant microservices with secure data enclave
CyberShield AI
Developed and deployed multiple systems including a 5-layer SME cybersecurity suite (scoring 78/100) and an offline C-based mesh communication network for emergency triage.
What these projects demonstrate
Production AI Systems
Ability to go beyond prototypes to build, deploy, and scale real-world generative AI and multimodal ML pipelines.
Scalable Cloud Infrastructures
Designing complex microservices and backend architectures using GCP, Azure, serverless deployments, and vector databases.
Full-Stack Autonomy
Working across the entire stack—from frontend UI/UX in Next.js to backend APIs in FastAPI, all the way to secure database schemas.
Practical Real-World Impact
Solving actual problems like clinical orchestration, offline mesh emergency networks, and crop disease mapping through system design.
Journey
Engineering Journey
From foundational systems to production-scale AI architectures — a progression of building, scaling, and refining real-world systems.
VaidyaOS Engineering & Deployment
Independent AI Healthcare Initiative
- Architected and engineered a comprehensive, privacy-first healthcare AI platform running directly on-device using quantized GGUF models.
- Developed full offline medical intelligence capabilities alongside cloud-synced fallback APIs, ensuring zero-latency, highly available clinical insights.
- ON-DEVICE AI
- OFFLINE-FIRST
- Llama.cpp
Meta PyTorch OpenEnv Grand Finale
Meta
- Cleared Round 1 from 52,000+ registered developers.
- Selected for the Grand Finale in Bangalore — one of the most competitive ML hackathons globally.
- ARCHITECTURE
- ML SYSTEMS
Event-Driven Microservices Engine
CareerLens & HealthMesh Core
- Designed and scaled an event-driven microservices architecture powering production AI platforms.
- Built parallel processing pipelines for vector embeddings and background workers, enabling reliable, low-latency operations across 32 independent services.
- Scaled to 32 microservices
- Reduced processing latency
- Enabled real-time AI workflows
Multi-Agent Supervisor Framework
TaskForze System
- Built a multi-agent orchestration framework with supervisor nodes to coordinate task execution across specialized agents.
- Implemented failover mechanisms and real-time escalation workflows using external APIs, ensuring reliability under SLA constraints.
- 5 specialized agents coordinated
- Zero-downtime failover triggers
- Automated WhatsApp/Call escalation
Core Library Contributor
Ubuntu, Pandas & NumPy
- Contributed to performance optimizations and bug fixes across Python data ecosystem libraries (Ubuntu, Pandas, NumPy).
- Resolved complex issues and improved system efficiency, earning multiple GitHub Pull Shark badges (22+ PRs merged).
- 22+ PRs successfully merged
- Performance bottlenecks resolved
- Strengthened major OSS pipelines
B.Tech CSE (AI & ML)
PES University, Bengaluru
- Focused on systems-level thinking including operating systems, networking, and low-level architecture (RISC-V, TCP/IP).
- Actively engaged in developer communities (GDG, NVIDIA Cloud) and technical speaking.
- Deep architectural fundamentals
- Systematic problem solving
- Community technical leadership
What This Journey Reflects
This timeline reflects my progression from learning foundational systems to designing and deploying scalable AI architectures. I consistently focus on building production-ready systems that integrate AI, robust cloud infrastructure, and real-world constraints to solve complex engineering challenges.
Impact Metrics
Achievements & Impact
Recognized through national competitions, real-world deployments, and continuous technical mastery.
Focused on building and validating real-world AI systems through competitions, production deployments, and continuous learning.
Google Gen AI Exchange
NATIONAL WINNER
Built an AI-driven clinical orchestration system. Selected among top teams nationwide for innovation, robust technical architecture, and real-world applicability.
Inferential 2.0
🥇 1st Place
Developed a high-performance system under intense time pressure. Praised for clean system design, scalability, and seamless integration capabilities.
Verified Credentials
Certifications Gallery
28 certifications across AI, Cloud, Security, and Development. Click any to view full resolution.
Gen AI Exchange Hackathon — Winner
Google Cloud × Hack2skill
Gen AI Academy APAC 2026
Google Cloud × Hack2skill
Gen AI Academy 2.0 — AI/ML Track
Google Cloud × Hack2skill
Gen AI Academy 2.0 — Networking Track
Google Cloud × Hack2skill
Gen AI Academy 2.0 — Cloud Architecture
Google Cloud × Hack2skill
Gen AI Academy 2.0 — Data Analytics Track
Google Cloud × Hack2skill
Gen AI Academy 2.0 — DevOps Track
Google Cloud × Hack2skill
Gen AI Academy 2.0 — Serverless Track
Google Cloud × Hack2skill
Gen AI Academy 2.0 — Security Track
Google Cloud × Hack2skill
Gen AI Academy 2.0 — Networking (Hack2skill)
Google Cloud × Hack2skill
Gen AI Academy 2.0 — Cloud Track (Hack2skill)
Google Cloud × Hack2skill
Gen AI Academy 2.0 — Data Analytics (Hack2skill)
Google Cloud × Hack2skill
Gen AI Academy 2.0 — AI/ML (Hack2skill)
Google Cloud × Hack2skill
5-Day AI Agents Intensive Course
Kaggle × Google
Gemini Certified Educator
Google for Education
Agentic AI Day
Google Cloud × Hack2skill
Inferentia 2.0 — 1st Place
PES University · AURA · AI&ML Dept
Meta PyTorch OpenEnv Hackathon — Round 1
Meta × OpenEnv × Scaler
Code of Honour 2.0
PESIT × Unstop
AWS Job Roles in the Cloud
Amazon Web Services
AWS Cloud Practitioner Essentials
Amazon Web Services
Frontend Developer (React)
HackerRank
JavaScript (Intermediate)
HackerRank
Oracle Cloud Infrastructure — Gen AI Professional
Oracle
AI for Beginners
HP LIFE Foundation
Responsible AI with GitHub Copilot
GitHub
NVIDIA Cloud & Community
NVIDIA
GDG Discovery Certification
Google Developer Groups
Get in Touch
Let's Build
Scalable AI Systems
I'm open to AI/ML internships, high-impact projects, and collaborations focused on real-world systems. Currently building production-grade AI platforms — happy to connect if you're working on something meaningful.
Based in Bengaluru, open to remote opportunities.