AI-Native Full Stack Engineer (SaaS Products)- Bangalore
Actively Reviewing the ApplicationsHYrEzy Tech Solutions
India, Karnataka, Bengaluru
Full-Time
On-site
INR 25–40 LPA
Posted 15 hours ago
•
Apply by June 7, 2026
Job Description
Role: AI-Native Full Stack Engineer (SaaS Products)
Build and ship SaaS products using AI-native development workflows. Depending on requirements, products may include AI-embedded features (LLM-powered automation, agentic workflows, intelligent document processing) or may be traditional SaaS built with AI-assisted development practices.
What You Will Build
- Location: Bangalore, Karnataka, India
- Experience: 3 - 5 Years
- Budget: 30 - 40 LPA
- What to include when sending profiles
- 2 – 3 shipped examples of AI/LLM features (what was built, stack used, outcome)
- GitHub/portfolio links
- JST overlap availability
Build and ship SaaS products using AI-native development workflows. Depending on requirements, products may include AI-embedded features (LLM-powered automation, agentic workflows, intelligent document processing) or may be traditional SaaS built with AI-assisted development practices.
What You Will Build
- Production SaaS features: end-to-end from UI to API to data model to deployment
- AI-embedded product capabilities where required: workflow automation, document intelligence, conversational interfaces
- Evaluation and monitoring systems for AI features (quality, latency, cost)
- Own full-stack delivery with minimal handoffs
- Integrate LLM APIs (OpenAI, Claude, etc.) into production applications
- Ship MVP-quality increments in 2–3-week cycles
- Collaborate with stakeholders in English; clarify scope, propose trade-offs, and iterate quickly
- Establish practical engineering standards: version control, testing, CI/CD, observability
- Full stack - React/Next.js + Node.js and/or Python; database design; API development
- AI-native workflow - Daily use of AI coding tools (Copilot, ChatGPT, Cursor, etc.) for development, debugging, iteration
- LLM integration - Hands-on experience integrating LLM APIs into real applications (not just prototypes)
- Delivery speed -Proven ability to ship working software in 2–3-week cycles
- Communication - Fluent English (written and verbal); remote-first collaboration discipline
- B2B SaaS or workflow automation experience
- Agentic workflow design (task decomposition, tool use, state management)
- RAG implementation and evaluation
- Cloud deployment (AWS/GCP), CI/CD, containerization
Required Skills
Communication
Engineering
Automation
Monitoring
Python
AWS
API Development
Next.js
GitHub
CI/CD
React
Testing
Debugging
RAG
Hiring
Document intelligence
Version control
Database Design
Workflow design
AI Coding Tools
Cloud deployment
Node
Embedded
Conversational
Cursor
Workflow Automation
Profiles
Data model
State management
OpenAI
Decomposition
SaaS products
ChatGPT
React/Next.js
Coding tools
LLM APIs
Node.js
Monitoring Systems
Observability
Trade
WAS
Notes
LLM
MVP
Claude
LLM Integration
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