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AI/LLM Engineering & Data & AI Integration

• Experienced AI Engineer specializing in Large Language Model (LLM) development and deployment with strong expertise in transformer architectures, fine-tuning techniques (LoRA, QLoRA), and Retrieval-Augmented Generation (RAG) systems.

• Proficient in building end-to-end AI pipelines, including data ingestion, embedding generation, vector search using Qdrant, and RESTful API integration via FastAPI and Streamlit. Skilled in prompt engineering and developing multi-agent orchestration systems using LangChain for complex, knowledge-driven workflows.

• Focused on scalable, production-ready AI solutions that integrate intelligent document processing, semantic search, and dynamic response generation.

• Data Engineering

• Over 10 years of experience in data engineering, with a strong emphasis on developing robust data pipelines using Python for automation and scripting, combined with advanced SQL expertise for querying, optimization, and relational database management.
• Specialized in designing and implementing modern data architectures, focused on scalability, performance, and high availability. This includes in-depth knowledge of cloud storage solutions, distributed computing frameworks, and both streaming and batch data processing pipelines for resilient and efficient data systems.
• More than 25 years of experience as a database architect and engineer/developer.
• Extensive experience in administering and working with highly transactional relational databases, including Microsoft SQL Server and PostgreSQL.
• Proficient in building ETL/ELT data pipelines utilizing Debezium and Kafka, targeting analytical databases such as Greenplum, Vertica, and Hadoop.
• Advanced programming skills in Python.

DevOps Engineering

• Skilled in containerization and orchestration tools, including Docker and Kubernetes.
• Experience working with Helm for Kubernetes package management.
• Hands-on experience with leading cloud platforms, including AWS and GCP.
• Proficient with infrastructure-as-code and configuration management tools, such as Ansible and Terraform.
• Strong understanding of CI/CD pipelines and GitOps workflows.
• Expertise in database administration for systems like PostgreSQL and Microsoft SQL Server.
• Familiarity with network protocols (TCP, IP, UDP) and routing protocols.
• Proficient in Python programming and Bash scripting.
• In-depth knowledge of Linux environments.

Database Management Systems (DBMS)

• Microsoft SQL Server (2000 - Latest Version)
• PostgreSQL (9.6 - Latest Version)

Database Development & Optimization

• Design and development of complex stored procedures, functions, triggers, and views
• Advanced indexing strategies, including clustered, non-clustered, full-text, and JSON/GIN indexes
• Expertise in query tuning and optimization using execution plans, query store, hints, and statistics
• Implementation of partitioning strategies for managing large datasets
• Optimization using columnstore indexes and in-memory OLTP

Database Programming & Query Languages

• T-SQL (Microsoft SQL Server)
• PL/SQL (Oracle)
• PL/PGSQL (PostgreSQL)

High Availability & Disaster Recovery

• Implementation of Always On Availability Groups (SQL Server)
• Experience with log shipping, database mirroring, and replication
• Failover clustering for both Windows and PostgreSQL environments
• Point-in-Time Recovery (PITR) and Write-Ahead Logging (WAL) archiving in PostgreSQL
• Development of comprehensive backup strategies, including full, differential, incremental, PITR, and snapshots

Security & Compliance

• Role-based access control (RBAC) and fine-grained permission management
• Implementation of Transparent Data Encryption (TDE) and row-level security
• Usage of Dynamic Data Masking and Always Encrypted features (SQL Server)
• Experience in data auditing and compliance with regulations such as GDPR and HIPAA
• Secure database configuration and vulnerability assessment practices

ETL & Data Integration

• Development using SQL Server Integration Services (SSIS)
• Use of PostgreSQL Foreign Data Wrappers (FDW)
• Expertise in data migration and transformation, including ETL pipelines, Change Data Capture (CDC), and bulk insert operations
• Proficiency in handling data formats including JSON, XML, and CSV

Infrastructure & Automation

• Automation through scripting using Python and Bash
• Infrastructure as code (IaC) for database environments using Terraform
• Deployment of containerized PostgreSQL databases with Docker
• Cloud-based database management across platforms such as Azure SQL, Amazon RDS, and Google Cloud SQL
• Monitoring and observability using Prometheus, Grafana, and SQL Server Profiler