EPAM is seeking a skilled Senior AI Python Engineer to join our Life Sciences and Healthcare projects, focusing on bioinformatics and data-driven solutions. This role is well-suited for engineers passionate about using Python, AI, and analytics to address challenges in biology and biomedicine. You will contribute to impactful projects with global pharmaceutical, biotech, and healthcare companies, working on solutions in bioinformatics, computational biology, genomics, and AI-enhanced drug discovery. You will participate in developing cloud-native platforms to process large-scale biomedical data, support research and drug development, and enable data-driven decision-making in regulated settings. Responsibilities Design, architect, and develop cloud-native, AI-driven solutions for Life Sciences using Python Build, optimize, and maintain data processing pipelines for large-scale biological and biomedical datasets (genomics, transcriptomics, proteomics, clinical data) Support the integration and application of Generative AI solutions, including LLMs and RAG, in bioinformatics and drug discovery workflows Utilize computational and statistical techniques for high-throughput biological data, including sequence-based and omics data Collaborate with bioinformaticians, computational biologists, data scientists, and domain experts to implement technical solutions based on scientific requirements Facilitate technical improvements, review code, and ensure high-quality documentation and maintainability Enhance AI components within client solutions and EPAM in-house platforms while following best practices for development processes Tackle challenges around data scale, security, and performance in computational life sciences applications Stay up to date with emerging trends in Life Sciences, AI, and cloud technologies, actively driving innovation within projects and teams Requirements 3+ years of experience in Python software engineering, along with practical exposure to Life Sciences, Healthcare, Bioinformatics, Computational Biology, or related domains Proficiency in Python and modern web/API frameworks (Django, Flask, FastAPI) Experience with scientific and analytical Python libraries (NumPy, Pandas, SciPy, scikit-learn) and/or a relevant M.Sc. or Ph.D. in Bioinformatics, Computational Biology, or a related quantitative field Exposure to handling biological, biomedical, or clinical data, including NGS, transcriptomics, proteomics, multi-omics, or genomic data formats (FASTQ, BAM, VCF) Familiarity with integrating AI / ML models into production systems in data-intensive or regulated contexts Strong understanding of software design principles, data structures, and algorithms Hands-on experience with cloud platforms (AWS, Azure, or GCP) Strong analytical and problem-solving skills, with the ability to contribute to technical discussions and solution design Excellent communication skills and experience working in cross-functional, international teams Fluency in English (both written and spoken) at a minimum B2 level
