About Massive Bio Every cancer patient deserves access to treatment options. Massive Bio is an AI-powered precision medicine platform transforming how cancer patients discover and access clinical trials by eliminating the barriers of geography, financial constraints, and information asymmetry that have historically limited enrollment.

Founded in 2015 and headquartered in US, Massive Bio is scaling its impact globally by powering operations across multiple countries and bringing innovative cancer treatment options to a rapidly growing and diverse population of patients. Through our proprietary AI platform, we connect individuals to clinical trials worldwide and partner with leading pharmaceutical companies, contract research organizations (CROs), and healthcare systems to accelerate drug development and expand equitable access to cutting-edge therapies.

We're recognized as a leader in health-tech innovation. Massive Bio was featured as #4 in Fast Company's Startup 100 list for Turkey and has raised $24M total funding from impact-driven investors including Revo Capital, the International Finance Corporation, and Cavendish Impact Foundation, validating both our business model and our mission-driven approach.

About The Role Reporting to the Software Development Director, you will design, build, and operate LLM-powered features end-to-end, including model customization, agent workflows, RAG pipelines, and scalable backend services, while ensuring reliability, security, and privacy compliance throughout.

What You’ll Do

• Fine-tune and customize Small and Large Language Models (LLMs) for domain-specific tasks (summarization, reasoning, classification, retrieval, etc.)
• Develop, test, and deploy AI agents using frameworks such as LangChain, LlamaIndex, or equivalent
• Build and maintain orchestration pipelines for LLM workflows (task routing, memory management, RAG pipelines)

Who You Are

• 5+ years of experience in AI/LLM applications
• Strong experience in Python, including frameworks such as FastAPI, Flask, or Django
• Hands-on experience with LLM fine-tuning, prompt engineering, model evaluation, and RAG pipelines
• Experience with vector databases
• Strong knowledge of PostgreSQL including schema design, optimization, indexing, and query tuning

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