Full Stack AI Engineer
Summary
AI Engineer with a foundation in full-stack development and hands-on experience building production-grade AI platforms. I specialize in RAG optimization, multi-LLM orchestration, semantic memory systems, and latency reduction, combining engineering rigor with AI innovation.
Ive designed and deployed systems that handle 100+ concurrent users, reduce AI response latency by 70%+, and improve grounding and hallucination control using HyDE-based strategies and topic-isolated memory. My background in MERN stack and Next.js allows me to prototype, build, and deploy end-to-end AI products with full ownership of the pipeline.
Pursuing a Bachelor's in Computer Science (AI & ML) at NED University, I actively participate in hackathons and coding competitions, applying AI knowledge to solve real-world challenges at scale.
I believe AI is more than modelsits about building intelligent systems that make meaningful decisions and impact lives. Im looking to collaborate on innovative AI solutions that push the boundaries of applied machine learning
Expectations
looking for a role where I can work on meaningful problems, take real ownership, and grow alongside a strong team. I value an environment that encourages thoughtful engineering, open communication, and continuous learning, especially when building AI-driven products that have real-world impact. I hope to collaborate with people who care about quality, challenge ideas respectfully, and move fast without losing sight of fundamentals. More than anything, I want a role where my work matters, my contributions are trusted, and I can keep improving both as an engineer and as a problem-solver.
Employment Preferences
Expected Base Salary
**,000 USD
Expected Total Compensation
**,000 USD
Academic Degree
Experience
Total Professional Experience
Startup Experience
Big-Tech Companies
Enterprise Experience
Skills
- AI Engineer
- Founding AI Engineer
- Full-Stack AI Engineer
- Full-Stack Engineer
- Machine Learning Engineer
- Applied AI
- Generative AI
- Large Language Models
- LLMs
- Retrieval Augmented Generation
- RAG
- RAG Optimization
- Semantic Search
- Vector Search
- Pinecone
- Vector Databases
- Embeddings
- HyDE Retrieval
- Hallucination Reduction
- Context Grounding
- AI Evaluation
- LLM Evaluation
- Relevance Scoring
- Agentic Workflows
- AI Orchestration
- Multi-Model Orchestration
- OpenAI API
- DeepSeek
- Together AI
- Llama Models
- Streaming AI Responses
- Async Pipelines
- AI Infrastructure
- AI Platform Architecture
- Microservices Architecture
- Distributed Systems
- Backend Engineering
- API Development
- REST APIs
- FastAPI
- Flask
- Node.js
- Express.js
- Python
- JavaScript
- TypeScript
- SQL
- PostgreSQL
- MySQL
- MongoDB
- Cloud Computing
- Google Cloud Platform
- GCP
- Microsoft Azure
- Docker
- CI
- CD Pipelines
- Vercel
- Cloud Cost Optimization
- Auto Scaling
- Request-Based Infrastructure
- WebSockets
- Real-Time Systems
- High-Traffic Systems
- Performance Optimization
- Caching Strategies
- System Design
- Scalable Systems
- Semantic Memory Systems
- Long-Term Memory
- Topic Isolation
- Context Management
- AI Memory Systems
- User Personalization
- Time-Based Decay Models
- Full-Stack Development
- React
- Next.js
- HTML5
- CSS3
- Tailwind CSS
- Mobile-First Design
- Responsive UI
- Booking Systems
- Notification Systems
- Real-Time Availability
- Software Engineering
- Agile Methodology
- Test-Driven Development
- TDD
- AI-Driven Development
- AIDD
- Git
- Version Control
- Leadership
- Technical Ownership
- Startup Engineering
- Founding Team
- Product Engineering
- End-to-End Development
- Production-Grade Systems
- AI Product Development
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