You will get a HIPAA-ready AI system for healthcare workflows and clinical automation
Project details
I deliver production-grade, HIPAA-ready AI systems specifically for healthcare workflows and clinical automation. Unlike generic AI developers, I build systems that run reliably in real clinical environments, integrating EHR/EMR data, automating medical documentation, and providing real-time predictive insights. My solutions are fully compliant, scalable, and optimized for accuracy, latency, and operational impact , not just demos.
Programming Languages
JavaScript, Python, JavaCoding Expertise
Cross Browser & Device Compatibility, Performance Optimization, SecurityWhat's included
| Service Tiers |
Starter
$1,500
|
Standard
$3,500
|
Advanced
$6,000
|
|---|---|---|---|
| Delivery Time | 7 days | 14 days | 30 days |
Number of Revisions | 1 | 2 | 2 |
Number of Pages | 1 | 3 | 5 |
Design Customization | - | - | |
Content Upload | - | - | - |
Responsive Design | |||
Source Code |
About Mohammad
AI/ML Engineer | AI Agents, RAG Systems, Data Engineering & MLOps
Queens County, United States - 5:40 pm local time
My work combines AI Engineering, Machine Learning, Data Engineering, NLP, and Automation Architecture to create scalable systems that are accurate, observable, maintainable, and cost-efficient.
Clients typically hire me when they need more than a prototype or chatbot:
• AI agents that execute tasks end-to-end
• Reliable RAG systems over private/company data
• Scalable ML & data pipelines
• LLM applications with strong retrieval accuracy
• Automation systems integrated into real operations
• Production-ready AI infrastructure with monitoring & optimization
If you're building AI-powered products, internal copilots, intelligent automation systems, or data-intensive ML platforms, I can architect and implement the full stack.
🧠 Core Expertise
AI Engineering & LLM Systems
• AI Agents & Autonomous Workflows
• Multi-Agent Architectures
• RAG (Retrieval-Augmented Generation) Systems
• AI Copilots & Internal Assistants
• Prompt Engineering & Prompt Chaining
• LLM Orchestration & Guardrails
• Structured Outputs & Function Calling
• Hallucination Reduction Techniques
• Context Management & Memory Systems
• Multi-Model Routing & Fallback Logic
• AI Workflow Automation
• NLP Applications & Text Processing
• Conversational AI Systems
• Document Intelligence & OCR Pipelines
• Semantic Search & Knowledge Retrieval
• Evaluation, Monitoring & Observability
Machine Learning & Data Science
• Machine Learning Pipelines
• Predictive Modeling
• Feature Engineering
• Model Deployment & Inference APIs
• Real-Time & Batch ML Systems
• Recommendation Systems
• NLP & Transformer-Based Systems
• Deep Learning Infrastructure
• AI/ML System Optimization
• ML Monitoring & Logging
• Statistical Analysis & Data Processing
• AI-Powered Analytics Solutions
Data Engineering & Infrastructure
• ETL / ELT Pipelines
• Real-Time Streaming Pipelines
• Event-Driven Architectures
• Data Lake & Cloud Storage Architectures
• API-Based Data Ingestion
• Data Cleaning & Transformation
• Workflow Orchestration
• Distributed Data Processing
• Schema Design & Data Modeling
• Data Infrastructure for AI Systems
• Batch & Streaming Analytics Pipelines
• Cloud-Native Data Platforms
🛠 What I Build
I design and implement:
• Autonomous & semi-autonomous AI agents
• High-accuracy RAG systems with vector search & re-ranking
• LLM workflows with guardrails, memory & structured outputs
• ML infrastructure from training to deployment
• ETL/ELT pipelines and event-driven data workflows
• Real-time analytics & streaming architectures
• AI-powered document processing & research systems
• Backend APIs, orchestration services & cloud infrastructure
⚙ Tech Stack
AI / ML / NLP:
GPT-4.1, GPT-4o, o3, Claude 3.x, Llama 3, Mistral, Hugging Face, Transformers, NLP Pipelines, Embeddings, Semantic Search
AI Frameworks:
LangChain, LlamaIndex, Agent Frameworks, RAG Architectures, Prompt Orchestration Systems
Data & Vector Infrastructure:
Pinecone, Weaviate, Chroma, Milvus, Supabase, SQL, Vector Search, Hybrid Retrieval Systems
Backend & APIs:
Python, FastAPI, Node.js, REST APIs, Webhooks, Microservices
Data Engineering:
Airflow, ETL Pipelines, ELT Workflows, Streaming Pipelines, Data Modeling, Workflow Automation
Cloud & Infrastructure:
AWS (Lambda, ECS, S3, RDS), Docker, Serverless, Modal, CI/CD Pipelines, GPU Optimization
Automation Platforms:
n8n, Make, Custom Orchestrators, API Integrations
📊 What Clients Value
• Production-focused AI architecture; not demo systems
• AI + Data Engineering expertise combined in one profile
• Reduced hallucination & higher retrieval accuracy
• Cost-efficient LLM pipelines & inference optimization
• Scalable ML & data infrastructure
• Clean architecture with maintainable codebases
• Reliable automation systems integrated into business operations
• Clear documentation, observability & smooth handoff
🚀 Typical Use Cases
• AI Agents for Operations & Support
• AI-Powered Internal Tools
• Enterprise Knowledge Assistants
• NLP & Document Processing Systems
• RAG Applications over Private Data
• AI Automation for Sales & CRM Workflows
• ML Infrastructure & Inference Systems
• Real-Time Analytics & Data Platforms
• AI-Driven Reporting & Research Systems
• Scalable Backend Systems for AI Products
If you're looking for an AI Engineer, ML Engineer, NLP Engineer, Data Engineer, or AI Automation Architect who can build reliable end-to-end systems from infrastructure to intelligent workflows, I can help.
Steps for completing your project
After purchasing the project, send requirements so Mohammad can start the project.
Delivery time starts when Mohammad receives requirements from you.
Mohammad works on your project following the steps below.
Revisions may occur after the delivery date.
Requirement Analysis & Planning
Review client’s workflow, data, and goals; define scope and compliance requirements (HIPAA/GDPR).
Data Assessment & Preparation
Analyze EHR/EMR data, perform cleaning, anonymization, and preprocessing for AI use.