GCP AI Engineer

Notice Period
:
Immediate joiners OR not longer than 30 days’ Notice Period.

We are seeking a highly skilled and motivated Senior AI/ML Engineer with deep, hands-on expertise in building custom AI models that can be deployed on Prem, and/or on Google Cloud Platform (GCP) to bridge the gap between Data Science research and Enterprise IT production.

In this role, you will be the architectural backbone of our AI practice. You will work across diverse AI fields—from traditional predictive analytics to cutting-edge Large Language Models (LLMs) and computer vision engines—deploying them into robust, highly available, and secure microservices on Prem and on GCP. Whether building a real-time REST API to intercept medical claims in milliseconds or orchestrating massive batch-scoring pipelines, your work will directly optimize operations.

• End-to-End ML model development along MLOps pipelines: design, develop, and implement production-ready CI/CD pipelines on GCP, encompassing data ingestion, feature engineering, model training, evaluation, and scalable deployment.
• GCP AI Architecture: leverage and orchestrate the full GCP data stack to build the organization’s AI infrastructure.
• Data & Features: build robust data pipelines and feature stores using Big Query and Dataflow / Apache Beam.
• Model Training & Registry: train and version control models using Vertex AI Workbench and the Vertex Model Registry.
• Deployment & Serving: deploy low-latency real-time inference using Vertex AI Endpoints and containerize lightweight deterministic rule engines using Cloud Run or Google Kubernetes Engine (GKE).
• Orchestration: schedule complex batch-scoring workflows using Cloud Composer (Apache Airflow).
• Hybrid Cloud AI Integration: design architectures that securely bridge on-premises data centers (Oracle/SQL) with GCP AI services using Cloud Interconnect, Apigee API gateways, or secure REST endpoints.
• Data Anonymization & Security: build on-premises data masking and tokenization pipelines (removing PHI/PII) before sending stateless inference requests to cloud-based LLMs.
• API & System Integration: wrap machine learning models in secure, high-performance RESTful APIs (e.g., FastAPI/Flask) to integrate with core claims processing engines and API gateways.
• Model Observability: implement Vertex AI Model Monitoring to track data drift, concept drift, and training-serving skew, ensuring models adapt to changing healthcare billing behaviors.
• Data Security & KSA Compliance: architect AI solutions that adhere to Saudi Arabian data sovereignty and healthcare regulations (SAMA, CHI, NDMO, PDPL). Implement Cloud DLP and VPC Service Controls to dynamically mask and secure PHI and National IDs.
• Cross-Functional Collaboration:
  
  partner with Data Scientists, investigators, medical SMEs, and product managers to translate clinical rules and business requirements into scalable technical solutions.

• Bachelor’s or Master’s degree in computer science, software engineering, artificial intelligence, or a related quantitative field.
• 3–5+ years of professional engineering experience with a track record of deploying ML models into production.
• Deep, hands-on mastery of Google Cloud Platform (GCP) for ML workloads.
• Strong proficiency in Python (OOP, modular design, unit testing) and libraries (Tensor Flow, PyTorch, scikit-learn, Pandas).
• Experience with backend API development frameworks (FastAPI, Flask) for high-throughput model serving.
• Strong Dev Ops fundamentals:
  Docker, Git, CI/CD tooling (Cloud Build, Git Hub Actions), and Infrastructure as Code (Terraform).
• Solid understanding of ML evaluation metrics (Precision, Recall, ROC-AUC) and model evaluation trade-offs.
• GCP
  
  Certifications:
  
  Professional Machine Learning Engineer or Professional Data Engineer.
• Healthcare/Insurance domain experience (medical billing codes such as ICD-10, CPT, DRG; NPHIES interoperability; claims adjudication; or FWA detection).
• Advanced AI experience with deploying LLMs, Agentic workflows (Lang Chain, Llama Index, CrewAI), or OCR systems in production.
• Localization: familiarity with Arabic NLP and processing localized text datasets.

If you are interested in this opportunity, please send your resume to (Use the "Apply for this Job" box below). and ensure the position name is included in the subject line.

Harnessing human insight to cut costs, fast-track tech adoption, and scale innovation globally.

• Flint International IT Services UAE, Burlington Tower, Office #905, Business Bay, Dubai, United Arab Emirates