G42
Data Scientist
- Permanent
- Abu Dhabi, United Arab Emirates
- Experience 2 - 5 yrs
Job overview
Date posted
08/10/2025
Location
Abu Dhabi, United Arab Emirates
Salary
AED 20,000 - 30,000 per month
Compensation
Comprehensive package
Experience
2 - 5 yrs
Seniority
Experienced
Qualification
Masters degree
Expiration date
22/11/2025
Job description
Presight (ADX-listed, majority-owned by G42) seeks a Data Scientist with applied machine learning experience and working knowledge of large language models (LLMs) to help design and implement production-ready AI solutions powering natural language interfaces, search, and knowledge-driven tools. The role contributes to AI Agent and Multi-Agent systems based on LLMs, including agent tool interfaces and integration with external systems and APIs; participates in prompt engineering using techniques such as Chain of Thought, ReAct, and context management strategies; develops RAG-based retrieval-augmented QA systems with domain-specific improvements; and collaborates on scalable frameworks for workflow, agent, and multi-agent coordination. The position requires proficiency in Python (data structures and algorithms), backend frameworks (FastAPI or similar), deep learning frameworks (PyTorch), containerization (Docker), relational and non-relational databases (PostgreSQL, Redis), Git and modern development workflows, with familiarity across LLMs, VLMs, Generative AI, agent system design, reasoning models, and Model Context Protocol (MCP). The role operates in a team-oriented, agile environment alongside senior scientists, engineers, and product managers, staying current with the latest AI and LLM advancements to enhance product features while leveraging AI tools (e.g., Cursor, Claude, copilots, ChatGPT) to accelerate delivery. Presight offers an inclusive, innovation-driven culture, high-impact projects, continuous learning, and competitive rewards including healthcare, education support, and leave benefits.
Required skills
Key responsibilities
- Contribute to the design and development of AI Agent and Multi-Agent systems based on LLMs to support autonomous decision-making and task execution.
- Participate in prompt engineering using techniques such as Chain of Thought, ReAct, and context management strategies to improve model performance.
- Support development of agent tool interfaces and integrate agents with external systems and APIs for end-to-end workflows.
- Build and enhance RAG-based retrieval-augmented QA systems and apply domain-specific model improvements.
- Collaborate on scalable frameworks for workflow, agent, and multi-agent coordination to enable reliable production deployment.
- Work closely with senior scientists, engineers, and product managers to deliver production-ready AI systems for natural language interfaces, search, and knowledge tools.
- Stay current with AI and LLM advancements and help apply state-of-the-art methods to improve product features and outcomes.
- Contribute code and components using Python, FastAPI (or similar), PyTorch, Docker, PostgreSQL, Redis, and Git within modern development workflows.
- Apply sound software engineering practices, including testing and version control, to ensure maintainable and reliable AI services.
Experience & skills
- Master’s or Ph.D. in Computer Science, Data Science, Machine Learning, Applied Mathematics, or related field.
- 3+ years of hands-on experience in AI, machine learning, or intelligent agent system development.
- Familiarity with LLMs, VLMs, Generative AI, and agent system design, including practical project experience building agent or multi-agent systems integrated with external systems or data sources.
- Understanding of reasoning models and Model Context Protocol (MCP).
- Knowledge of agent tools, retrieval-augmented generation (RAG), workflow orchestration, and prompt engineering techniques (e.g., Chain of Thought, ReAct).
- Proficiency in Python with solid foundations in data structures and algorithms.
- Experience with backend frameworks (FastAPI or similar) and deep learning frameworks (PyTorch).
- Experience with containerization tools (Docker) and databases (PostgreSQL, Redis).
- Comfort with Git and modern development workflows in a team-oriented, agile environment.
- Ability to leverage AI tools (e.g., Cursor, Claude, copilots, ChatGPT) to improve efficiency and productivity, with strong communication and collaboration skills and a growth mindset.
