About ITGOALS

ITGoals is an Egypt-based enterprise software and technology delivery company with 17+ years of enterprise delivery experience. We provide dedicated engineering teams, ERP and SAP services, product engineering, software development, and outsourcing / nearshore delivery for organizations across the GCC, Europe, the United States, and the wider region. Our financial-services work includes secure platforms and technology delivery supporting banking, payments, digital channels, integration, data, and financial operations.

Job Title

AI Engineer

Location

Cairo, Egypt (hybrid/work-from-office supported; international collaboration as needed)

Years of Experience

5+ years in AI/ML or related roles

Job Description

As an AI Engineer at ITGoals, you will design, build, integrate, and operationalize AI and machine-learning capabilities that enhance digital experiences, analytics, operational efficiency, and intelligent automation. You will work within enterprise-grade environments, ensuring security, governance, explainability, and maintainability from development through production. You’ll collaborate with business and technology stakeholders, data engineers, backend developers, architects, QA, and security teams to deliver robust AI-enabled solutions integrated into enterprise workflows and channels.

Key Responsibilities

Work with business and technology stakeholders to translate defined use cases into practical AI/ML solution approaches and measurable technical outcomes.
Prepare, clean, transform, and analyze data required for model development, experimentation, evaluation, and production inference.
Develop, train, fine-tune, or integrate machine-learning models using appropriate Python-based libraries and frameworks.
Build APIs or application components that expose AI capabilities to enterprise systems, digital channels, workflows, or internal tools.
Design evaluation approaches covering model quality, robustness, latency, reliability, and business-relevant performance metrics.
Implement logging, monitoring, versioning, reproducibility, and controlled promotion of models or AI services into production environments.
Work with engineering and platform teams on containerization, deployment, scaling, CI/CD, and MLOps practices as appropriate to the solution.
Apply responsible-AI principles, data privacy, access controls, model governance, and human-review mechanisms where required by the use case.
Investigate model drift, data issues, unexpected outputs, performance bottlenecks, and integration failures and support corrective action.
Document model assumptions, training / evaluation data, dependencies, interfaces, limitations, and operational support requirements.
Collaborate with data engineers, backend developers, architects, QA, security, and business stakeholders throughout delivery.

Required Experience

Hands-on experience developing AI, machine-learning, or advanced analytics solutions using Python.
Experience taking models or AI services beyond experimentation into integrated application or production use.
Practical understanding of data preparation, model evaluation, API integration, and software-engineering practices.
Ability to communicate model behavior, limitations, and trade-offs clearly to technical and non-technical stakeholders.

Required Skills

Python
Machine-learning fundamentals
One or more ML frameworks such as scikit-learn, PyTorch, TensorFlow, or equivalent
Data preparation and feature engineering
SQL and data analysis
Model evaluation and performance measurement
REST APIs / service integration
Git and collaborative software development
Production monitoring and MLOps awareness
Security, privacy, and responsible-AI awareness

Banking / Fintech & Nice to Have

Banking, fintech, payments, fraud, risk, customer service, operations, or other regulated financial-services AI experience is a strong advantage.
Generative AI, LLM application development, prompt engineering, RAG, embeddings, or vector-search experience.
Docker, Kubernetes / OpenShift, cloud AI services, or model-serving platforms.
Experience with model governance, explainability, bias assessment, or human-in-the-loop workflows.
Experience integrating AI solutions with enterprise workflow or customer-facing applications.

What Success Looks Like

Builds AI capabilities that are measurable, supportable, and integrated into real business processes.
Understands that production AI requires engineering, governance, monitoring, and security in addition to model quality.
Can challenge weak use cases and explain technical trade-offs without unnecessary complexity.

ITGOALS Offers

Enterprise-scale assignments where engineering quality, security, resilience, and delivery discipline matter.
Structured ITGoals recruitment, onboarding, delivery governance, and clear professional ownership throughout the engagement.
Collaboration with experienced engineers, architects, QA professionals, delivery leaders, and business stakeholders.
Exposure to complex digital-transformation environments and the opportunity to deepen banking, fintech, payments, and regulated-enterprise experience.
Opportunities to contribute to long-term enterprise delivery programs based on performance, business demand, and role fit.

Application Instructions

Share an updated CV with the ITGoals recruitment team, highlighting the experience most relevant to this role, particularly enterprise delivery, banking / fintech exposure where applicable, and the technologies listed above. Shortlisted candidates will be contacted for the next stage of the recruitment process.

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