Applied AI Engineer - Financial Services

Job Summary:
We are looking for an AI Software Engineer to design, build, and deploy cutting-edge AI/ML solutions for financial services. This role involves working on fraud detection, risk assessment, robo-advisory, LLM-based applications, and cloud-native AI systems. The ideal candidate will have 5+ years of software development experience and at least 2+ years in AI/ML production environments, with expertise across ML frameworks, cloud infrastructure, and full-stack engineering. You will collaborate with product, data science, and compliance teams to deliver innovative, scalable, and compliant AI solutions.

Key Responsibilities:

• Design, develop, and deploy AI/ML models for financial applications (fraud detection, risk assessment, robo-advisory, etc.).
• Build and optimize end-to-end ML pipelines (data ingestion → preprocessing → deployment → monitoring).
• Implement LLM-based solutions using OpenAI, Anthropic, Hugging Face, LangChain, LlamaIndex.
• Develop and maintain cloud-native architectures (AWS, GCP, Azure).
• Apply MLOps best practices: CI/CD for ML, automated testing, observability.
• Collaborate with product managers, data scientists, and compliance teams.
• Drive rapid prototyping through POCs and MVPs.
• Ensure compliance with cybersecurity and regulatory standards (explainable AI, bias detection, SAMA).
• Contribute to open-source projects and stay updated with AI/ML advancements.

Requirements:
Essential Qualifications:

• 5+ years of professional software development experience.
• 2+ years of hands-on experience in AI/ML production environments.
• Expertise in AI/ML frameworks (TensorFlow, PyTorch, scikit-learn).
• Proficiency with LLM frameworks (OpenAI, Anthropic, Hugging Face, LangChain, LlamaIndex).
• Experience in prompt engineering, fine-tuning, and RAG architectures.
• Strong knowledge of MLOps pipelines, CI/CD practices, and model deployment.
• Advanced proficiency with cloud platforms (AWS, GCP, or Azure).
• Familiarity with Infrastructure as Code (Terraform, CloudFormation, Pulumi).
• Solid experience with backend & frontend development (Node.js, FastAPI, Django, React, Next.js, etc.).
• Knowledge of databases, APIs, container orchestration (Kubernetes, Docker), and DevOps tools.

Preferred Qualifications:

• Experience in AI solutions for financial services.
• Knowledge of edge AI and device-level inference optimization.
• Background in quantitative finance or algorithmic trading.
• Familiarity with blockchain / distributed ledger technologies.
• Publications, research contributions, or conference presentations in AI/ML.
• Proficiency in Arabic NLP and language models (technical skill, not necessarily spoken fluency).
• Previous startup or venture studio experience.
• Domain expertise in computer vision, NLP, time-series forecasting, or recommender systems.

Critical Competencies:

• Builder Mentality: Focused on delivering working AI systems, not just designs.
• Problem-Solving: Ability to tackle complex, ambiguous challenges with speed.
• Technical Leadership: Influences design and architecture decisions.
• Innovation Drive: Passion for applying cutting-edge AI in real-world fintech use cases.
• Rapid Prototyping: Skilled at building POCs and MVPs to validate ideas.
• Collaboration: Strong communicator, effective with cross-functional teams.
• Learning Agility: Continuously stays ahead of AI/ML advancements.
• Pragmatic Approach: Balances technical excellence with business priorities and time-to-market.