AI Software Engineer

9 Minutes ago • 5 Years +
Research Development

Job Description

We are seeking an AI Software Engineer to design, build, and deploy cutting-edge AI/ML solutions for financial services. This role focuses 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 2+ years in AI/ML production, with expertise across ML frameworks, cloud infrastructure, and full-stack engineering. Collaboration with product, data science, and compliance teams is essential to deliver innovative, scalable, and compliant AI solutions.
Good To Have:
  • 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.
  • Previous startup or venture studio experience.
  • Domain expertise in computer vision, NLP, time-series forecasting, or recommender systems.
Must Have:
  • Design, develop, and deploy AI/ML models for financial applications.
  • Build and optimize end-to-end ML pipelines.
  • Implement LLM-based solutions using OpenAI, Anthropic, Hugging Face, LangChain, LlamaIndex.
  • Develop and maintain cloud-native architectures (AWS, GCP, Azure).
  • Apply MLOps best practices, including CI/CD and observability.
  • 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.
  • Knowledge of databases, APIs, container orchestration, and DevOps tools.

Add these skills to join the top 1% applicants for this job

cross-functional
risk-management
risk-assessment
forecasting-budgeting
game-texts
automated-testing
react
prototyping
aws
azure
terraform
model-deployment
fastapi
data-science
scikit-learn
pytorch
computer-vision
node.js
ci-cd
docker
kubernetes
django
next.js
tensorflow

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.

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.

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