I’m a Senior Mobile Engineer with 7+ years of experience building and shipping production-grade mobile applications, primarily with Flutter, with a growing focus on Generative AI, RAG, LLM applications, and Agentic AI systems.

I enjoy working at the intersection of mobile engineering, backend systems, automation, and AI — turning complex requirements into scalable, reliable products.

• 📱 Build large-scale Flutter applications from architecture to production
• 🏗️ Design maintainable systems using Clean Architecture, modularity & scalable patterns
• 🤖 Build GenAI applications using LLMs, RAG, agents and tool calling
• 🔗 Develop AI agents & multi-step workflows with LangGraph
• 🧠 Work with vector databases, embeddings, retrieval pipelines & semantic search
• ⚙️ Build backend services with Python & FastAPI
• 🔄 Automate development workflows, testing, releases and engineering operations
• 👨‍💻 Mentor developers, review architecture and code, and contribute to technical direction

Flutter · Dart · Android · GetX · Dio · Firebase · REST · gRPC · Deep Linking

LLMs · RAG · Agentic AI · LangGraph · LangChain · Google ADK · MCP · Tool Calling · Embeddings · Vector Databases

Python · FastAPI · REST APIs · Firebase · GCP · Docker · Supabase · CI/CD

Clean Architecture · Modular Architecture · Git · GitHub · GitLab · Fastlane · Testing · CI/CD · Observability

I'm currently going deeper into production-grade AI engineering, particularly:

LLMs
 ├── RAG
 │    ├── Retrieval
 │    ├── Embeddings
 │    ├── Vector Databases
 │    └── Reranking
 │
 ├── Agentic AI
 │    ├── LangGraph
 │    ├── Tool Calling
 │    ├── Multi-Agent Systems
 │    └── Human-in-the-Loop
 │
 ├── AI Engineering
 │    ├── Evaluation
 │    ├── Observability
 │    ├── Guardrails
 │    └── Production Security
 │
 └── AI + Software Engineering
      ├── Code Agents
      ├── Automated Debugging
      ├── QA Automation
      └── Developer Productivity

An AI-powered engineering workflow that investigates application crashes and helps automate the path from Crashlytics → root-cause analysis → code changes → merge request → QA.

Concept:

Crashlytics
     ↓
Stack Trace Analysis
     ↓
Source Code Detection
     ↓
Git History / Blame
     ↓
LLM Analysis
     ↓
Confidence Check
     ↓
Code Fix
     ↓
Human Review
     ↓
Merge Request
     ↓
Build & QA

Built around Python + LangGraph + LLMs + Git + CI/CD, with a strong focus on human-in-the-loop engineering workflows.

An AI assistant designed around enterprise operational knowledge and workflows.

Exploring:

• RAG pipelines
• Enterprise knowledge retrieval
• Agentic workflows
• Tool calling
• MCP
• Role-based access
• Guardrails
• Observability
• Human approval workflows

Building an AI-driven personal finance experience around:

• Expense tracking
• Monthly planning
• Financial insights
• Intelligent recommendations
• Personalized purchasing/wishlist decisions

Combining Flutter + Python + AI workflows to explore practical AI applications beyond chat interfaces.

Exploring autonomous workflows that can help engineering teams:

Requirements → Test Cases → Test Execution → Issue Detection → Jira → Developer Workflow

The goal is not simply to generate code, but to build AI systems that can participate in real software-engineering workflows.

I believe good software is not just about writing code.

It's about:

Architecture → Reliability → Performance → Automation → Developer Experience → User Experience

I particularly enjoy solving problems where scale, performance, reliability and automation intersect.

• 📱 7+ years of mobile development experience
• 🚀 Built and shipped large-scale production Flutter applications
• 👥 Experience mentoring developers and contributing to technical leadership
• 🏗️ Strong background in scalable mobile architecture
• 🔐 Experience with application security and production hardening
• ⚡ Performance optimization for resource-constrained devices
• 🔄 CI/CD, automated builds and production release workflows
• 🤖 IBM Generative AI Engineering / RAG & Agentic AI training
• 🐍 Expanding from mobile engineering into AI & backend engineering

🎓 IBM Generative AI Engineering Professional Certificate

Focused on:

RAG · LLMs · LangChain · LangGraph · Vector Databases · Agentic AI · Multi-Agent Systems · Tool Calling

I'm particularly interested in building the next generation of software where:

        ┌─────────────────┐
        │    AI Agents    │
        └────────┬────────┘
                 │
       ┌─────────┼─────────┐
       ↓         ↓         ↓
    Mobile    Backend    Tools
       │         │         │
       └─────────┼─────────┘
                 ↓
        Intelligent Systems

My long-term focus is on AI-powered software engineering, agentic systems, and intelligent product experiences — while bringing the engineering discipline I've developed from building production mobile applications.

I'm interested in:

• 🤖 GenAI & Agentic AI
• 📱 Mobile Engineering
• 🏗️ Software Architecture
• ⚙️ Developer Productivity
• 🧪 AI-powered QA & Automation
• 🚀 Building practical AI products

If you're working on something interesting in these areas, feel free to connect.

Build. Automate. Learn. Repeat. 🚀