You will get a production-ready AI system with LLMs, RAG, agents, and Python
Top Rated
Project details
Most AI projects fail because they stop at prediction. I build systems that act.
I'm Tilek - a Lead Data Engineer and Senior AI/ML Engineer with 15+ years of experience delivering production-grade AI systems, LLM applications, and large-scale data platforms. I've helped Scale AI cut LLM data prep time by 70%, built document processing systems saving 60% processing time, and designed pipelines serving enterprises at national scale.
I build agentic AI systems that integrate into your product, execute real workflows, and deliver measurable outcomes from day one.
This project can include:
— LLM apps: RAG systems, AI agents, ChatGPT/Llama integrations
— ML models: prediction, classification, fraud & anomaly detection
— NLP: document processing, contract analysis, semantic search
— AI-powered APIs and backend systems with FastAPI
— Data pipelines: Spark, Kafka, Airflow, BigQuery, Snowflake
— MLOps: deployment, monitoring, CI/CD — MLflow and Kubeflow
— Cloud: AWS, GCP, Azure — Docker, Kubernetes, Terraform
Every project starts with your business goals - not code.
🚀 Message me with your project - let's build AI that works in production.
I'm Tilek - a Lead Data Engineer and Senior AI/ML Engineer with 15+ years of experience delivering production-grade AI systems, LLM applications, and large-scale data platforms. I've helped Scale AI cut LLM data prep time by 70%, built document processing systems saving 60% processing time, and designed pipelines serving enterprises at national scale.
I build agentic AI systems that integrate into your product, execute real workflows, and deliver measurable outcomes from day one.
This project can include:
— LLM apps: RAG systems, AI agents, ChatGPT/Llama integrations
— ML models: prediction, classification, fraud & anomaly detection
— NLP: document processing, contract analysis, semantic search
— AI-powered APIs and backend systems with FastAPI
— Data pipelines: Spark, Kafka, Airflow, BigQuery, Snowflake
— MLOps: deployment, monitoring, CI/CD — MLflow and Kubeflow
— Cloud: AWS, GCP, Azure — Docker, Kubernetes, Terraform
Every project starts with your business goals - not code.
🚀 Message me with your project - let's build AI that works in production.
Machine Learning Tools
Amazon SageMaker, Apache Spark, Apache Spark MLlib, BERT, ChatGPT, Databricks Platform, fastText, Google AutoML, GPT-3, H2O, Kubeflow, MLflow, NLTK, NumPy, NVIDIA AI Platform, Open Neural Network Exchange, OpenCV, pandas, Python, PyTorch, scikit-learn, SciPy, TensorFlow, Vertex AI, XGBoostWhat's included
| Service Tiers |
Starter
$1,500
|
Standard
$6,000
|
Advanced
$18,000
|
|---|---|---|---|
| Delivery Time | 3 days | 7 days | 14 days |
Number of Revisions | 1 | 2 | 3 |
Number of Model Variations | 1 | 2 | 3 |
Number of Scenarios | 1 | 2 | 3 |
Number of Graphs/Charts | 0 | 1 | 2 |
Model Validation/Testing | |||
Model Documentation | - | ||
Data Source Connectivity | - | - | |
Source Code |
Optional add-ons
You can add these on the next page.
Additional Revision
+$50
Model Documentation
(+ 1 Day)
+$100
Data Source Connectivity
(+ 1 Day)
+$100
2 reviews
(2)
(0)
(0)
(0)
(0)
This project doesn't have any reviews.
JF
Jonathan F.
Aug 18, 2026
SAP FSM Consultation
MP
Marina P.
Apr 15, 2026
Python Developer
About Tilek
AI Developer AI Agent AI Chatbot Developer AI Python Developer SQL
100%
Job Success
Abu Dhabi, United Arab Emirates - 3:57 pm local time
🏆 Top Rated Plus | 100% Job Success | $55K+ earned on Upwork | trusted with production systems
I'm Tilek - AI Developer, AI Agent Developer, Python Developer, Machine Learning Developer, Data Engineer, Data Scientist. 15+ years shipping Artificial Intelligence, AI Development, Python, SQL, Data Engineering for Scale AI, Hitachi Energy, Fortune.
30+ ETL Pipeline deployments. 10M+ API calls daily. 99.9% uptime on Amazon Web Services. Terabyte-scale SQL in Snowflake and PostgreSQL.
AI Developer, 50+ AI Development projects: production Artificial Intelligence with Python, PostgreSQL, Amazon Web Services. AI Development covers RAG, LLM orchestration, Computer Vision, Automation-ready RESTful API. AI Development stands on Data Engineering - clean SQL, tested ETL Pipeline, documented Data Modeling.
AI Agent Development, 25+ AI Agent Development systems: LangChain, LangGraph, MCP. AI Agent Development covers tool calling, multi-agent orchestration, error handling. AI Agent Development in Python, Node.js and TypeScript as RESTful API and API Integration. AI Agent Development over SQL warehouses and Snowflake data.
Generative AI Developer, RAG Developer, LLM Developer: OpenAI API, Anthropic Claude API, pgvector, Pinecone. Embeddings from SQL and Snowflake sources, served as RESTful API in Docker. AI Development and AI Agent Development inside production products.
Machine Learning Developer, NLP: Machine Learning models for classification, forecasting, Computer Vision. Natural Language Processing pipelines in Python with evaluation sets and quality gates before release.
Python Developer, 15+ years: Python backend with Django, Flask, FastAPI. RESTful API design, API Integration, PostgreSQL, SQL, Amazon Web Services, Docker. Python powers AI Development, Data Engineering, Machine Learning, Automation.
Data Engineer, 30+ Data Engineering platforms: production ETL Pipeline work in Python, SQL, Snowflake, PostgreSQL, Amazon Web Services. Data Engineering covers ingestion, Data Modeling, orchestration, Docker deployment, cost tuning. Data Engineering under Artificial Intelligence products.
ETL Pipeline Engineer, 30+ pipelines in production: Python and SQL transformations, incremental loads into Snowflake, PostgreSQL and BigQuery, backfills and retries as RESTful API jobs in Docker. ETL Pipeline orchestration in Airflow and dbt, with quality gates and alerts before users see bad data.
SQL and Data Modeling, 25+ warehouses: advanced SQL, window functions, cost tuning in Snowflake and PostgreSQL. Data Modeling with star schema, slowly changing dimensions, bronze-silver-gold layers. Data Modeling contracts tested in CI.
Data Scientist, Data Analyst, 25+ engagements: Python, SQL, PostgreSQL for Data Modeling, Data Engineering handoffs, Artificial Intelligence experiments, Data Analyst dashboards.
Automation Engineer, 90%+ manual reduction: Automation with Python, Node.js, API Integration. Web Scraping into ETL Pipeline stages, document and workflow Automation in Docker.
INDUSTRY IMPACT
AI Agent platform, RAG knowledge base, LLM orchestration - 25+ agent systems in production with Python, LangChain, LangGraph, pgvector, RESTful API.
Data platform, ETL Pipeline, Data Modeling - 30+ pipelines in Snowflake and PostgreSQL, Airflow orchestration, SQL cost tuning on Amazon Web Services.
Document Automation, OCR, Computer Vision - 2K+ documents/day with Python, Machine Learning, AI Development, API Integration, Docker.
Healthcare, FinTech, EdTech - Artificial Intelligence, AI Agent Development, Data Engineering with PostgreSQL, SQL, Amazon Web Services.
TECHNICAL STACK
Python | Artificial Intelligence | AI Development | AI Agent Development | Machine Learning | Natural Language Processing | LangChain | OpenAI API | Chatbot Development | SQL | ETL Pipeline | Data Engineering | Snowflake | PostgreSQL | Data Modeling | Node.js | API Integration | RESTful API | Amazon Web Services | Automation
HAVE A COMPLEX AI PROBLEM OR A BROKEN DATA PIPELINE? CONTACT ME.
AI Developer | AI Developers | AI Agent Developer | AI Chatbot Developer | AI Automation Developer | AI Integration Developer | AI App Developer | AI SaaS Developer | LLM Developer | RAG Developer | Generative AI Developer | OpenAI Developer | Claude Developer | LangChain Developer | Python AI Developer | AI Python Developer | Machine Learning Developer | NLP Developer | AI Engineer | AI Architect | AI Consultant | AI Data Engineer | Python Developer | Data Engineer
Steps for completing your project
After purchasing the project, send requirements so Tilek can start the project.
Delivery time starts when Tilek receives requirements from you.
Tilek works on your project following the steps below.
Revisions may occur after the delivery date.
Requirements & Use Case Analysis
Understanding your business goals, data, and defining the best AI/ML or LLM approach for your use case.
Solution Architecture Design
Designing scalable architecture, selecting models, tools, and defining how the AI system will work in production.