Al Integration Developer

Role Overview

AI Integration Developer at VAM Systems, Bahrain operations.

Role Purpose

Develop and integrate AI models with enterprise applications, leveraging machine learning frameworks and cloud platforms to build scalable, production-ready AI solutions that bridge AI capabilities with backend systems and business requirements.

Key Responsibilities

Machine Learning Development

• Develop and train Supervised, Unsupervised Learning, Classification, Regression, and Clustering models.
• Perform Model Training, Validation, and Evaluation.
• Execute Feature Engineering and Optimization.
• Tune and monitor model performance.
• Build conversational AI and Chatbots.
• Develop document processing systems.
• Handle large data sets such as Healthcare and Genomics data.
• Design and implement data preprocessing pipelines for structured and unstructured data.

Large Language Models & Prompt Engineering

• Work with Large Language Models (LLMs) such as GPT and Claude.
• Design and implement Prompt Engineering solutions.
• Build Retrieval-Augmented Generation (RAG) systems.
• Integrate Vector databases such as Pinecone, FAISS, and Weaviate.

Cloud & MLOps

• Deploy, monitor, and scale AI models in production.
• Design cloud-based AI architectures.
• Manage AWS SageMaker, AWS NextFlow, AWS Bedrock, AWS Lambda, Amazon S3, and IAM.
• Implement MLOps practices, Docker containerization, and CI/CD pipelines.

API & Backend Development

• Develop RESTful APIs to integrate AI models with enterprise applications.
• Design and develop backend services and API integrations within .NET-based applications.
• Build API-first design solutions.
• Support integration with microservices architecture.

.NET Development

• Leverage Microsoft .NET technologies including ASP.NET Core, Blazor, MVC, Web APIs, and Entity Framework.
• Design .NET application architecture and database integration.
• Implement authentication and security concepts.
• Deploy applications in cloud-based environments.

Technical Documentation & Stakeholder Management

• Prepare technical documentation, architecture diagrams, and solution designs.
• Explain technical and AI concepts clearly to non-technical stakeholders.
• Provide effective communication and maintain documentation standards.

Production Support

• Support production systems and critical deployments.
• Provide operational support when required.
• Work under structured project environments similar to government and RFP frameworks.

Qualifications & Experience

• Strong understanding of Supervised and Unsupervised Learning, Model Training, Validation, and Evaluation, and Feature Engineering.
• Practical knowledge of Large Language Models (LLMs) such as GPT and Claude.
• Experience building conversational AI, Chatbots, and document processing systems.
• Hands-on experience with AWS SageMaker, AWS NextFlow, AWS Bedrock, AWS Lambda, Amazon S3, and IAM.
• Experience handling large data sets such as Healthcare and Genomics data.
• Exposure to healthcare, licensing, or insurance domain systems.
• Ability to work under structured project environments similar to government and RFP frameworks.

Skills & Competencies

• Strong expertise in TensorFlow, PyTorch, and Scikit-learn.
• Expertise in Retrieval-Augmented Generation (RAG) and Vector databases such as Pinecone, FAISS, and Weaviate.
• Advanced knowledge of Prompt Engineering.
• Proficiency in RESTful API development.
• Strong experience with Microsoft .NET technologies including ASP.NET Core, Blazor, MVC, Web APIs, and Entity Framework.
• Competency in SQL and NoSQL databases.
• Expertise in Git version control.
• Proficiency in Docker containerization and CI/CD pipelines.
• Strong MLOps practices knowledge.
• Familiarity with Microservices architecture and API-first design.
• Understanding of .NET application architecture, database integration, and authentication and security concepts.
• Strong problem-solving and analytical thinking.
• Ability to clearly explain technical and AI concepts to non-technical stakeholders.
• Effective communication and documentation skills.
• Team-oriented mindset.

Additional Information

• Willingness to support production systems, critical deployments, and provide operational support when required.