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% Skill category
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\skillfeatured{LLM Engineering}{3 years production}

\skilldetail{APIs}{OpenAI GPT-3.5/4, Anthropic Claude}\\[2pt]
\skilldetail{Workflows}{prompt engineering, RAG pipelines, context management, safety guardrails, content filtering}\\[2pt]
\skilldetail{Infrastructure}{production deployment, latency optimization, monitoring, cost optimization}\\[2pt]
\skilldetail{Specialization}{therapeutic chatbots, conversational AI, safety systems}\\[2pt]

\vspace{5pt}

\skillcat{Programming}

\begin{itemize}
\item Python (10+ years production)
\item Clojure (10+ years)
\item Rust (5+ years)
\item Go (3+ years)
\item Elixir (2+ years)
\item Java, R, SQL (advanced), bash
\end{itemize}

\vspace{3pt}

\skillcat{ML/AI}

\begin{itemize}
\item Frameworks: PyTorch, TensorFlow, Keras, scikit-learn, XGBoost, LightGBM, CatBoost
\item NLP: spaCy, NLTK, Hugging Face Transformers
\item Deep Learning: CNNs, RNNs, LSTMs, GRUs, Transformers, attention mechanisms, transfer learning, fine-tuning
\end{itemize}

\vspace{3pt}

\skillcat{Cloud \& Infrastructure}

\begin{itemize}
\item AWS: EC2, S3, SageMaker, Lambda
\item GCP: GCE, GCS, GKE
\item Containers: Docker, Kubernetes
\end{itemize}

\vspace{3pt}

\skillcat{Databases}

\begin{itemize}
\item PostgreSQL (expert)
\item MongoDB, Redis, Neo4j, SQLite, MySQL
\end{itemize}

\vspace{3pt}

\skillcat{Data Engineering}

\begin{itemize}
\item Apache Spark, Apache Airflow, Kafka
\item ETL pipelines, data quality, orchestration
\end{itemize}

\vspace{3pt}

\skillcat{Web \& APIs}

\begin{itemize}
\item Flask, FastAPI, Django
\item REST APIs, microservices architecture
\end{itemize}

\vspace{3pt}

\skillcat{DevOps}

\begin{itemize}
\item git, Linux, CI/CD (GitHub Actions, Jenkins)
\item Monitoring, logging
\end{itemize}

\vspace{3pt}


% ============================================
% DOMAIN EXPERTISE
% ============================================
\vspace{5pt}

\skillcat{Domain Expertise}

\domain{LLM Production Systems}{3 years • }{Therapeutic chatbots, safety systems, prompt engineering, RAG pipelines}

\domain{Quantitative Finance}{2+ years • }{Level 2 market data, PIN/VPIN algorithms, order flow analysis, backtesting}

\domain{Healthcare AI}{1 year • }{Medical NER, clinical terminology, HIPAA compliance, decision support tools}

\domain{Financial NLP}{1 year • }{SEC filings analysis, knowledge graphs, entity linking, sentiment analysis}


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% LANGUAGES
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\section*{Languages}

{\color{TextSecondary}
English (Fluent), Russian (Native), French (Conversational), German (Conversational), Czech (Conversational), Hebrew (Basic)
}

\end{document}