Simplifying IT
for a complex world.
AI Engineer
Vlad S.
7+ years of experience
Europe
Can start immediately
AI Engineer
Vlad S.
7+ years of experience
Europe
Can start immediately
Domains
- Artificial intelligence
- Biomedical systems
- Healthcare data processing
- Enterprise software
Skills
AI and LLM Systems:
Backend and API Development:
Databases and Search:
Education
MSc in Computational and Applied Mathematics
English
C1 — confident in professional communication
Profile
Vladislav is an AI engineer with 7 years of experience building NLP systems, RAG applications, and LLM-assisted backend services in the biomedical domain. Works across Python-based AI pipelines, asynchronous LLM interaction, information retrieval systems, and NLP model development. Scope of work includes biomedical text analysis, vector and graph search, recognition model training, and AI workflow automation.
Experience
BostonGene | Senior Software Engineer
Biomedical NLP and LLM Systems
(Jun 2024 – Present)
- Created GitLab CI pipelines to automate application deployment workflows
- Implemented asynchronous interaction with LLMs through Amazon Bedrock using aioboto3
- Added summary validation workflows with readability scoring and length control through tool-calling mechanisms
- Developed a Flask application for generating summaries of molecular events in patient datasets
- Built Python-based backend solutions using Linux and containerized environments
BostonGene | Software Engineer
RAG and Biomedical NLP Systems
4 years (Jul 2020 – Jun 2024)
- Developed a RAG application with vector and graph search using LangChain
- Trained models for the recognition of drug side effects, frequency, and severity in FDA label datasets
- Implemented comorbidity recognition workflows mapped to ICD10 codes
- Developed NLP tools for analysis of oncology-related datasets and research workflows
BostonGene | Junior Software Engineer
NLP APIs and Recognition Systems
1 year (Jul 2019 – Jul 2020)
- Developed and maintained APIs for NLP-related web services
- Trained a SpaCy-based model for cell line recognition using Cellosaurus datasets
- Improved text segmentation workflows using SpaCy and NLTK
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+ 44 1509 733445
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