Al Integration Developer

VAM Systems
Manama
Workplace: OnsiteFull timeFunction: Software EngineeringSkills: ["Problem-solving","Analytical thinking","Communication","Documentation","Team-oriented mindset","Stakeholder communication"]

Design, build, and deploy AI integrations for enterprise applications, translating machine learning and LLM capabilities into production-ready backend services. Work across model training, validation, feature engineering, and MLOps, using TensorFlow/PyTorch/Scikit-learn and AWS tools like SageMaker, Bedrock, Lambda, and S3. Implement RESTful APIs, microservices, data preprocessing pipelines, and RAG/vector database solutions, with strong documentation and stakeholder communication.

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FursaFursa
VAM Systems
VAM Systems
15 hours ago

Al Integration Developer

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI
Last checked: 12 hours agoStatus: Live

Job Summary

Design, build, and deploy AI integrations for enterprise applications, translating machine learning and LLM capabilities into production-ready backend services. Work across model training, validation, feature engineering, and MLOps, using TensorFlow/PyTorch/Scikit-learn and AWS tools like SageMaker, Bedrock, Lambda, and S3. Implement RESTful APIs, microservices, data preprocessing pipelines, and RAG/vector database solutions, with strong documentation and stakeholder communication.
Location: Manama
Workplace: Onsite
Employment Type: Full time
Job Function: Software Engineering

Key Responsibilities

  • •Build and integrate AI models with enterprise applications via RESTful APIs and backend service development.
  • •Develop and deploy AI solutions in production, including monitoring, scaling, and operational support for critical deployments.
  • •Implement ML/LLM pipelines: data preprocessing for structured/unstructured data, model training/validation/evaluation, and feature engineering.
  • •Create RAG and chatbot/document processing systems using vector databases and prompt engineering approaches.
  • •Design cloud-based AI architectures, microservices, and .NET application components; prepare technical documentation, architecture diagrams, and solution designs.

Key Requirements

  • •Strong understanding of supervised/unsupervised learning, model training, validation, evaluation, and feature engineering/optimization.
  • •Experience with classification, regression, and clustering models, including model performance tuning and monitoring.
  • •Practical knowledge of LLMs (e.g., GPT, Claude), prompt engineering, and Retrieval-Augmented Generation (RAG) with vector databases (Pinecone, FAISS, Weaviate).
  • •Hands-on development with TensorFlow, PyTorch, and Scikit-learn, plus building conversational AI/chatbots and document processing systems.
  • •Strong backend and cloud integration skills: RESTful APIs, microservices/API-first design, SQL/NoSQL, and .NET (ASP.NET Core, Blazor/MVC, Web APIs, Entity Framework), with AWS tools (SageMaker, NextFlow, Bedrock, Lambda, S3) and MLOps/CI/CD, Docker, and production deployment/monitoring.
Experience:HealthcareGenomicsMLOpsLLMsRAG
Skills:Problem-solvingAnalytical thinkingCommunicationDocumentationTeam-oriented mindsetStakeholder communication
Languages:English
Tech Stack:Supervised LearningUnsupervised LearningModel TrainingModel ValidationFeature EngineeringClassificationRegressionClusteringLarge Language Models (LLMs)GPTClaudePrompt EngineeringRetrieval-Augmented Generation (RAG)Vector DatabasesPineconeFAISSWeaviateChatbotsDocument processingTensorFlow

Company Brief

VAM Systems
Provides product engineering and software development services across embedded systems, IoT, cloud, AI, and digital transformation for enterprises in automotive, healthcare, industrial, and consumer electronics sectors.
Industry: Professional Services
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