Role Profile
Section I: Basic Information
- Role Title: GenAI Engineer (Junior): Business Intelligence & AI
- Reporting Manager Title: Lead Data Scientist (Manager): Business Intelligence & AI
- Sector: Technology
- Division: Data & AI
- Department: Business Intelligence & AI
- Job Level: Senior Officer / Officer
Section II: Role Purpose
As part of Saudi Arabia’s drive toward digital transformation under Vision 2030, Cody Software Solutions is partnering with a leading financial institution in the Kingdom to hire a talented GenAI Engineer (Junior).
In this exciting role, you will be at the forefront of building and deploying next-generation AI solutions — from intelligent assistants to advanced Retrieval-Augmented Generation (RAG) systems — that enhance customer experience, enable smart decision-making, and support the bank’s innovation journey.
Section III: Key Responsibilities / Accountabilities
Core Responsibilities:
- Build GenAI-driven POCs from scratch, such as personal assistants, chatbots, copilots, and more.
- Contribute to the development and fine-tuning of large language models (LLMs) and other GenAI models for financial applications.
- Design and implement intelligent agents (conversational, orchestrator, worker agents, etc.).
- Process and analyze structured and unstructured financial data to train and optimize GenAI models.
- Implement and optimize Retrieval Augmented Generation (RAG) pipelines.
- Develop and refine effective prompting strategies for LLMs, optimizing performance for specific financial tasks.
- Test, evaluate, and analyze LLM and GenAI model performance, providing insights and recommendations for improvement.
- Contribute to model evaluation and monitoring.
- Collaborate with data scientists, engineers, and business stakeholders.
- Participate in end-to-end implementation of GenAI projects.
- Learn and apply best practices for GenAI development.
- Ensure personal information and security policies are respected when handling training or test data.
- Ensure compliance with Responsible AI guidelines and explainable AI standards.
Reporting:
- Prepare all relevant reports accurately and on time, in line with departmental policies and standards.
Cybersecurity Roles & Responsibilities:
- Implement and act in accordance with the partner’s information security policies.
- Protect assets from unauthorized access, disclosure, modification, destruction, or interference.
- Execute designated security processes or activities.
- Ensure accountability for all actions taken.
- Report security incidents, potential threats, or risks to the Cybersecurity team.
Section IV: Key Interactions
Internal:
- Coordinate regularly with team members to ensure operational efficiency, share best practices, and contribute to process improvements.
- Assist in preparing reports and updates for senior management, ensuring alignment with departmental goals and strategies.
External:
- Maintain communication with industry professionals to stay updated on market trends, best practices, and developments.
- Support engagement with regulatory authorities by ensuring compliance and assisting in documentation and reporting.
Section V: Qualifications & Experience
Knowledge
Minimum Qualifications:
- Proven record of practical implementation using GenAI, covering LLMs fine-tuning, RAG, LLMOps, prompt engineering, AI agents, and Agentic AI.
- Preferably experience in the banking sector.
- Excellent Python programming skills and familiarity with relevant libraries.
- Experience with prompt engineering and optimizing LLM outputs.
- Experience in Deep Learning within Natural Language Processing and Large Language Models.
- 3+ years of ML and Deep Learning experience or equivalent.
- Bachelor’s degree in a STEM field (Mathematics, Computer Science, Engineering).
- Excellent knowledge of data science tools (Python, SQL) and production environments.
- Understanding of probability and statistics fundamentals.
- Excellent communication and collaboration skills.
- Knowledge of LangChain, LlamaIndex, or other GenAI frameworks.
- Ability to develop and support MLOps systems.
- Understanding of MLOps concepts such as continuous training, monitoring, and improvements.
- Familiarity with GenAI models and architectures.
- Understanding of NLP and text processing techniques (desirable).
- Experience with cloud computing platforms (AWS, Azure, GCP) is a plus.
- Experience with financial data and applications.
Professional Certifications:
- Foundational Python or SQL.
- Data Analytics Fundamentals (e.g., Google, LinkedIn, Coursera).
Language Skills:
- Fluency in Arabic and English (additional languages are a plus).
Experience:
- 2–4 years in GenAI, deep learning, or analytics support roles.
Section VI: Competencies
Core Competencies:
- Driving Success
- Collaboration
- Customer Centricity
- Digital Mindset
- Effective Communication
Technical Competencies:
- Python Packages: Pandas, NumPy, Scikit-learn, Transformers, LangChain.
- Deep Learning Frameworks: TensorFlow, PyTorch.
- LLMs: LLaMA, Gemini, GPT-4, or other models.
- Vector Databases: PostgreSQL with vector extensions; other databases a plus.
- Cloud Platforms: AWS, Azure, GCP.
- Version Control: Git.
- Familiarity with Big Data Infrastructure & Pipelines, Data Governance, Advanced Data Modeling, Data Analytics, Cross-functional Collaboration, User-centric Design, Scalable Data Platforms, and BI Tools (Power BI, MS Excel).
