Angad Singh

Software Engineer

Bengaluru, Karnataka, India2 mos experience

AI EnabledAI ML Practitioner

Key Highlights

Expert in building scalable backend systems.
Innovated AI solutions improving data processing efficiency by 30%.
Strong focus on performance and reliability in software engineering.

Stackforce AI infers this person is a Backend Engineer specializing in AI-driven applications within the Healthcare and SaaS industries.

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Skills

Core Skills

Backend EngineeringAiData Analytics

Other Skills

distributed systemsAI-driven applicationshealthcare data analyticsML algorithmsSQLControl SystemsMySQLJavaScriptVoice AIDjango REST FrameworkPostgreSQLVector DatabasesQdrantChromadbTypeScript

About

I’m a Software Engineer 1 @ Intuit focused on building reliable backend systems and AI-driven applications that solve real-world problems at scale. My work spans backend engineering, distributed systems, and LLM-powered applications, including building real-time systems, hybrid RAG pipelines, and data-intensive platforms handling large-scale workloads. I enjoy working at the intersection of systems and intelligence—where performance, reliability, and decision quality matter. Previously, I’ve built: 1. AI systems processing 1M+ data points with semantic retrieval. 2. Real-time pipelines with low-latency streaming and concurrency handling. 3. Backend systems optimized for scalability and performance (up to 75% improvements). I’m particularly interested in agentic AI, scalable architectures, and high-performance systems, and I enjoy taking end-to-end ownership from design to production. Always learning, and Always building.

Experience

2 mos

Total Experience

2 mos

Average Tenure

2 mos

Current Experience

Intuit

Software Engineer 1

Apr 2026 – Present · 2 mos · Bengaluru, Karnataka, India · Hybrid

backend engineeringdistributed systemsAI-driven applicationsAI

Smartinternz

AI/ML Intern

Aug 2023 – Nov 2023 · 3 mos · Hyderabad · Remote

Innovated a healthcare data analytics platform by integrating data sources, optimizing backend workflows, and implementing efficient ML algorithms.
Improved data processing efficiency by 30% and improved disease detection accuracy to 85%+ by streamlining ETL processes and optimizing SQL queries.
Collaborated with front-end developers to design a user-friendly interface using JavaScript, integrating custom DL models for disease detection, resulting in a 20% increase in user engagement and enhanced platform versatility, employing Agile methodology.

healthcare data analyticsML algorithmsSQLAIdata analytics