14.07.2026 aktualisiert
100 % verfügbar
Senior Software Engineer | Data Engineering, Backend, AI/LLM Systems
Oberndorf am Neckar, Deutschland
Weltweit
MSc BioengineeringÜber mich
15+ years building large-scale data systems. Python, Go, Java, SQL/NoSQL, Docker, Linux. Recent focus: AI infrastructure LLM grounding, RAG, vector search, knowledge graphs. Domain depth in life sciences/pharma.
Skills
AI AgentsBioinformatikGenomicsUi-DesignPythonMachine LearningBioinformatik-HarvesterData ScienceGolang
Bioinformatics & Biomedical Data Systems
Expertise in RNA-seq, NGS, genomics, proteomics, cheminformatics, drug-target prediction, BLAST, Ensembl, UniProt, ChEMBL, GO, NCBI, and EBI resources. Development of large-scale biomedical data platforms handling over 1 billion biological entries.
AI & Machine Learning for Biomedical Applications
Proficiency in LLM grounding, Retrieval-Augmented Generation (RAG), Model Context Protocol (MCP), AI agents, knowledge graphs, vector search with Qdrant (75M+ vectors), embeddings, scikit-learn, statistical modeling, and predictive modeling.
Software Engineering & Programming
Strong command of Python, Go, Java, R, Rust, JavaScript, TypeScript, Bash, and SQL. Full-stack development from data integration to deployed production tools, including REST APIs and programmatic access frameworks.
Data Engineering & Knowledge Graphs
Data integration, ETL pipelines, knowledge graph construction integrating 80+ databases, Apache Lucene, vector databases, MapReduce, LMDB, RDBMS, MySQL, NoSQL, and large-scale dataset management.
DevOps & Infrastructure
Experience with Docker, Snakemake, Nextflow, Conda, Singularity, GitHub Actions, GitLab CI/CD, Git, Linux, HPC clusters, and REST APIs for reproducible and scalable bioinformatics workflows.
Cloud Platforms
Practical experience with AWS, Azure, and Google Cloud Platform for deploying and operating biomedical data services.
Multi-Omics Research & Computational Pipelines
Development of computational pipelines for inferring RNA-binding protein motif impact on alternative splicing and polyadenylation, multi-level models in R for transcription factor activity inference from RNA-seq data.
Microfluidics & Organ-on-Chip Prototyping
Prototype design of pressure-driven microfluidic systems for organ-on-chip experiments, including 3D component design, electronics, control software, and PDMS chip fabrication.
Expertise in RNA-seq, NGS, genomics, proteomics, cheminformatics, drug-target prediction, BLAST, Ensembl, UniProt, ChEMBL, GO, NCBI, and EBI resources. Development of large-scale biomedical data platforms handling over 1 billion biological entries.
AI & Machine Learning for Biomedical Applications
Proficiency in LLM grounding, Retrieval-Augmented Generation (RAG), Model Context Protocol (MCP), AI agents, knowledge graphs, vector search with Qdrant (75M+ vectors), embeddings, scikit-learn, statistical modeling, and predictive modeling.
Software Engineering & Programming
Strong command of Python, Go, Java, R, Rust, JavaScript, TypeScript, Bash, and SQL. Full-stack development from data integration to deployed production tools, including REST APIs and programmatic access frameworks.
Data Engineering & Knowledge Graphs
Data integration, ETL pipelines, knowledge graph construction integrating 80+ databases, Apache Lucene, vector databases, MapReduce, LMDB, RDBMS, MySQL, NoSQL, and large-scale dataset management.
DevOps & Infrastructure
Experience with Docker, Snakemake, Nextflow, Conda, Singularity, GitHub Actions, GitLab CI/CD, Git, Linux, HPC clusters, and REST APIs for reproducible and scalable bioinformatics workflows.
Cloud Platforms
Practical experience with AWS, Azure, and Google Cloud Platform for deploying and operating biomedical data services.
Multi-Omics Research & Computational Pipelines
Development of computational pipelines for inferring RNA-binding protein motif impact on alternative splicing and polyadenylation, multi-level models in R for transcription factor activity inference from RNA-seq data.
Microfluidics & Organ-on-Chip Prototyping
Prototype design of pressure-driven microfluidic systems for organ-on-chip experiments, including 3D component design, electronics, control software, and PDMS chip fabrication.
Erfahrung
Berufserfahrung0 - 5 Jahre
Freelancer seit2026
Sprachen
DeutschGrundkenntnisseEnglischverhandlungssicherTürkischMuttersprache
Projekthistorie
Built and operate sugi.bio, a platform for grounded biomedical AI serving live RAG and LLM-grounding queries (approximately 400 agent calls per day). Developed BioBTree v2, a biomedical knowledge graph integrating 80+ databases with an LLM-grounding interface and MCP server. Created Sugi Predict for drug-target prediction across approximately 30M patent compounds using RDKit fingerprints and vector search (Qdrant, 75M+ vectors). Built Sugi Atlas with 52,000 deterministic reference pages for genes, drugs, and diseases. Developed Enju for workflow orchestration for humans, AI agents, and compute. Authored four preprints on the systems and their methods (2026).
Contributed to MAPP, a computational pipeline inferring RNA-binding protein motif impact on alternative splicing and polyadenylation (Nature Communications, 2024). Developed multi-level models in R for inferring transcription factor activity from RNA-seq data. Built modular Snakemake workflows with Conda and Singularity for reproducible bioinformatics processing on HPC clusters.
Led prototype design of a pressure-driven microfluidic system for organ-on-chip experiments, including 3D component design, electronics, control software, and PDMS chip fabrication.