Senior AI Engineer
Future Look ITC
Role:Role Purpose
Lead the end-to-end development of AI capabilities, from understanding business problems and preparing data to building, evaluating, deploying, and improving models in production. Connect the company’s data annotation and quality workflows with reliable AI products and services. Set sound technical direction, work closely with product, software engineering, QA, and DevOps teams, and ensure that delivered solutions are useful, measurable, secure, scalable, and maintainable.
Key Responsibilities:
· Lead technical discovery and translate product and business needs into AI system designs, implementation plans, and clear acceptance criteria.
· Select and build appropriate machine learning, deep learning, and generative AI approaches, including use of pretrained or foundation models where suitable.
· Design data preparation and training workflows, including dataset validation, versioning, feature or prompt management, and reproducible experiments.
· Partner with Data Annotators and project leads to define labeling schemas, annotation guidance, sampling approaches, and review workflows that produce dependable training and evaluation data.
· Build evaluation frameworks using appropriate automated and human review methods; measure task quality, model accuracy, robustness, safety, and business usefulness.
· Investigate model errors and data quality issues, identify root causes, and improve the data, annotation, prompts, retrieval, model, or application layer as appropriate.
· Develop and integrate production-ready AI services, APIs, and workflows, including relevant LLM patterns such as retrieval-augmented generation when required by the use case.
· Deploy and operate AI workloads on cloud platforms, including Alibaba Cloud and/or Google Cloud Platform (GCP), in collaboration with DevOps and software engineering teams.
· Apply MLOps practices for repeatable training and deployment, model and dataset versioning, automated testing, release control, and rollback.
· Monitor production quality, latency, reliability, and cost; establish feedback and incident processes to detect drift and guide continuous improvement.
· Work with QA to include AI-specific testing such as representative data coverage, regression evaluation, edge cases, and human review where appropriate.
· Apply security, privacy, access control, and responsible AI practices throughout the data and model lifecycle; document designs, limitations, and operational guidance.
· Provide technical leadership through architecture reviews, code reviews, mentoring, and practical standards for the AI engineering team.
Qualifications and Experience:
· Bachelor’s or master’s degree in Computer Science, Artificial Intelligence, Data Science, or a related field, or equivalent practical experience.
· Substantial professional experience building and deploying machine learning or AI systems, including responsibility for production outcomes.
· Strong Python skills and experience with common data and machine learning libraries; hands-on experience with PyTorch, TensorFlow, or equivalent frameworks.
· Experience with model training or fine-tuning, data preparation, evaluation design, and production inference.
· Knowledge of machine learning and generative AI evaluation, data quality, experiment tracking, and model monitoring.
· Experience with one or more relevant areas such as large language models, natural language processing, computer vision, or recommendation systems.
· Practical experience designing APIs or integrating AI components into software products and services.
· Experience with Alibaba Cloud and/or Google Cloud Platform (GCP), containers, CI/CD, or MLOps is strongly preferred.
· Ability to lead technical initiatives and communicate complex AI tradeoffs clearly to technical and business stakeholders.
· Experience with Arabic-language data or AI applications is an advantage when relevant to product and customer needs.