LLM Engineer (to Yerevan)

BostonGene is redefining cancer patient care and drug development through the integration of omnimodal data and artificial intelligence. Built and validated through an extensive real-world clinical testing network, BostonGene’s Foundation Model of cancer and the immune system integrates genomic, transcriptomic, and immune data with clinical outcomes to generate biologically grounded, actionable insights. These insights enable biopharma partners to design and de-risk trials, identify novel targets, and optimize therapeutic response prediction across all stages of development while simultaneously improving patient care through clinically integrated innovation.

Position Summary:

We are looking for an LLM Engineer specializing in Agentic AI. Ideal candidate is a highly skilled Computational Scientist or Biologist with strong engineering expertise. This role involves collaborating with scientists and engineers to develop and deploy data engineering solutions based on LLMs, VLMs, and Agents. The primary goal is to refine our computational tools, thereby accelerating and enhancing BostonGene's clinical and pharmaceutical projects.

Please note that this position requires relocation to Armenia (relocation support provided).

Job responsibilities:

As an LLM Engineer, you will be responsible for advancing our internal platform's artificial intelligence capabilities, focusing on clinical research data. Your key tasks will include:

• AI Development & Deployment: Develop, improve, and deploy cutting-edge AI approaches , such as complex text summarization, timepoint extraction, retrieval/reranking systems, and Retrieval-Augmented Generation (RAGs), on clinical research datasets.
• Model Building & Fine-tuning: Build and fine-tune models, and set up swarms of AI agents using both internal and external data sources. Ensure performance evaluation is rigorous, employing clean code and state-of-the-art machine learning technologies.
• Agentic AI: Design and deploy Agentic AI solutions.
• Collaboration & Communication: Work closely within an international context with Computational Scientists, Data Engineers, Software Engineers, UX Designers, and Research Scientists, particularly those in core scientific platforms focused on protein therapeutics.
• Technical Leadership & Awareness: Maintain a deep understanding of the latest developments in data science, bioinformatics, and the state-of-the-art in AI/ML/DL algorithms and research results.
• Code Contribution & Review: Actively contribute to code repositories by developing new code, conducting peer code reviews, and debugging system issues.
• Data Governance: Ensure that the data used with different AI tools is maintained properly, and is never exposed to an uncompliant tool/toolset.

Required qualifications:

• Bachelor’s, preferably Master’s or PhD degree in Computer Science, Bioinformatics, Biomedical Engineering, or a related field.
• At least 2 years of experience in NLP, Computational Data Science, or a related field.
• Demonstrated experience with Python-based text analysis.
• Strong analytical and problem-solving skills.
• Good communication skills, both written and verbal, in English or Russian languages.
• Ability to work collaboratively in a multidisciplinary team.
• Attention to detail and a commitment to producing high-quality work.

Technical skills:

• Proficiency in Python programming language.
• Strong understanding of LLM and agentic AI concepts, including RAGs and BM25.
• Experience with PyTorch, langchain/langgraph. (PyTorch is a main framework used by division).
• Familiarity with text analysis techniques used in biological and medical research.
• Knowledge of machine learning algorithms and their application to data.
• Ability to handle large datasets and perform statistical/basic ML analysis.
• Proficiency in using data visualization tools such as Matplotlib, Seaborn, or similar.
• Experience in external model API integration.

What we offer:

• Relocation support;

• Comfortable office in the center of Yerevan, next to "Druzhba" metro station;

• Health insurance (comprehensive coverage including medical, dental, and vision plans);

• Flexible / hybrid work options (hybrid format, flexible hours);

• Professional development (support for trainings, workshops, conferences, and further education);

• Business trips (opportunities to build partnerships, attend conferences, and support the company's global presence);

• Staff referral program (bonuses for referring suitable candidates);

• Meals (free or subsidized meals, snacks, and beverages at the workplace).