AI Engineer – iBridge ERP / Antares Fintech (Bahrain)

Location: Manama, Bahrain

Role Type: Full-time (On-site)

Domains: FinTech, ERP Automation, AI/ML Engineering, Computer Vision, RAG/LLMs

1. Role Overview As an AI Engineer, you will work on building production-grade AI solutions for iBridge ERP and Antares Fintech’s automation platforms. You will develop, optimize, and deploy AI models for CV, NLP, Generative AI, anomaly detection, and data intelligence across ERP, finance, supply chain, and commodity trading environments. This is a hands-on engineering role involving model training, data pipelines, cloud deployment, and integration with enterprise systems.

2. Key Responsibilities

A. AI Model Development ● Build and fine-tune ML/DL models using PyTorch/TensorFlow. ● Develop object detection & tracking pipelines (YOLO family, RT-DETR, OpenCV). ● Create NLP, LLM, and RAG-based applications using LangChain, Transformers, ChromaDB, vector embeddings. ● Develop speech-to-text and multimodal pipelines (Whisper, ASR, OCR). ● Build anomaly detection, forecasting, risk scoring, and predictive ML models.

B. Data Engineering & Pipelines ● Build data ingestion & preprocessing pipelines (PySpark, SQL, APIs). ● Handle large datasets including financial, transactional, time-series, and video data. ● Work with Snowflake, Azure Blob, AWS S3, GCP buckets for model data workflows.

C. MLOps & Deployment ● Containerize models using Docker, deploy to AWS/Azure/GCP. ● Build scalable microservices using FastAPI. ● Deploy workloads using cloud compute (EC2, GKE, AKS) and cloud storage. ● Implement versioning, monitoring, and performance tuning for production AI systems.

D. Integration Into ERP & FinTech Systems ● Integrate AI functionalities into iBridge ERP workflows such as ○ invoice analysis, ○ procurement automation, ○ fraud/risk detection, ○ CV-based identity verification, ○ conversational AI assistants for ERP users.

E. Collaboration ● Work with CTO , Senior AI Engineer , and product teams. ● Participate in architecture discussions, feasibility analysis, and solution design. ● Present model metrics, accuracy improvements, and deployment strategies.

3. Skills Required

Core Technical Skills ● Python, NumPy, Pandas, Scikit-learn ● PyTorch / TensorFlow ● Computer Vision: YOLOv8, RT-DETR, OpenCV ● NLP & LLMs: Hugging Face Transformers, LangChain, RAG, Chroma/FAISS ● Speech: Whisper STT, OCR frameworks ● PySpark & big data handling ● FastAPI for API development

Cloud & MLOps ● AWS / Azure / GCP deployment workflows ● Docker, CI/CD basics ● Working with Snowflake / cloud databases ● Understanding of data pipelines & cloud architecture

Soft Skills ● Strong problem-solving ● Ability to convert research to production ● Clear explanation of model logic and trade-offs ● Willingness to own end-to-end delivery 4. You Are a Strong Fit If You Can ● Train, evaluate, and deploy AI models independently ● Handle both CV and LLM-based pipelines ● Break down a business workflow and propose an AI-driven automation ● Work with real-world noisy data from ERP, finance, or operations ● Deploy models on cloud infrastructure ● Build backend ML microservices (FastAPI, containerization) ● Communicate technical details clearly to founders

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