The Role
Leads and mentors AI engineering teams while providing technical direction across the AI software development lifecycle. Oversees the design, development, testing, optimization, and deployment of machine learning, generative AI, and intelligent automation solutions. Reviews architecture and code, manages technical risks, ensures engineering standards, drives process improvement, and partners with product and engineering stakeholders to deliver scalable, secure, and maintainable AI applications.
Summary Generated by Built In
Responsibilities
- Lead, mentor, and manage AI engineering teams, fostering a culture of collaboration, innovation, and continuous learning.
- Provide technical leadership and guidance throughout the AI software development lifecycle.
- Collaborate with Product Managers, Architects, and Engineering teams to translate requirements into scalable AI solutions.
- Guide the design, implementation, testing, and deployment of AI applications and machine learning solutions.
- Review solution designs, architecture, and code to ensure quality, scalability, security, and maintainability.
- Support engineering teams in solving complex technical challenges and making sound technical decisions.
- Ensure adherence to engineering standards, coding best practices, and AI development guidelines.
- Oversee the delivery of AI projects, ensuring quality, timelines, and technical excellence.
- Drive continuous improvement in software engineering processes, development practices, and AI solution quality.
- Guide the development, optimization, and deployment of machine learning models and Generative AI applications.
- Conduct technical reviews, mentor engineers, and support their professional growth.
- Identify technical risks and proactively drive mitigation plans.
- Strong understanding of Artificial Intelligence, Machine Learning, Deep Learning, and Generative AI concepts.
- Experience with Large Language Models (LLMs) and modern AI application architectures.
- Knowledge of Agentic AI concepts, AI orchestration, and intelligent automation.
- Experience with Retrieval-Augmented Generation (RAG), embeddings, and vector databases.
- Experience with model fine-tuning, optimization, and inference strategies.
- Experience with REST APIs, microservices, and distributed systems.
- Familiarity with Docker, Kubernetes, CI/CD, and cloud platforms (Azure, AWS, or GCP).
- Knowledge of MLOps, LLMOps, model monitoring, and AI observability.
- Understanding of AI security, governance, and responsible AI principles.
- Strong leadership and people management skills.
- Excellent communication and stakeholder management abilities.
- Strategic thinking with strong analytical and problem-solving capabilities.
- Ability to manage multiple priorities in a fast-paced environment.
- Strong mentoring, coaching, and team development skills.
- Excellent decision-making and organizational skills.
- Ability to influence technical direction across multiple teams.
- Bachelor's degree in Computer Science, Artificial Intelligence, Software Engineering, Data Science, or a related field. A Master's degree is a plus.
- Minimum 8 years of experience in software engineering, AI, or machine learning.
- At least 3 years of experience leading AI or software engineering teams.
- Proven experience delivering AI solutions from concept through production deployment.
- Experience managing cross-functional engineering teams and collaborating with product and business stakeholders.
- Hands-on experience with modern AI technologies, machine learning frameworks, and Generative AI solutions.
Skills Required
- Bachelor's degree in Computer Science, Artificial Intelligence, Software Engineering, Data Science, or a related field
- Minimum 8 years of experience in software engineering, AI, or machine learning
- At least 3 years of experience leading AI or software engineering teams
- Proven experience delivering AI solutions from concept through production deployment
- Experience managing cross-functional engineering teams and collaborating with product and business stakeholders
- Hands-on experience with modern AI technologies, machine learning frameworks, and generative AI solutions
- Strong understanding of artificial intelligence, machine learning, deep learning, and generative AI concepts
- Experience with large language models and modern AI application architectures
- Knowledge of agentic AI, AI orchestration, and intelligent automation
- Experience with retrieval-augmented generation, embeddings, and vector databases
- Experience with model fine-tuning, optimization, and inference strategies
- Experience with REST APIs, microservices, and distributed systems
- Familiarity with Docker, Kubernetes, CI/CD, and cloud platforms such as Azure, AWS, or GCP
- Knowledge of MLOps, LLMOps, model monitoring, and AI observability
- Understanding of AI security, governance, and responsible AI principles
- Master's degree in a related field
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The Company
What We Do
Raya Holding for Financial Investments is an investment holding firm that builds and scales businesses across technology, fintech, business process outsourcing, retail and distribution, manufacturing, automotive, food processing, and hospitality. It operates through a portfolio of flagship companies and subsidiaries in six countries, serving customers in more than 50 countries. The group says its investments focus on innovation, sustainable long-term value, digital transformation, and economic opportunity.
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