AI Engineer

This is a remote position.

We are looking for a skilled and practical AI Engineer to design build and maintain local AI agents private datasets and intelligent automation solutions for our internal operations and customer-facing projects.

The ideal candidate should be able to work with Large Language Models local AI deployment retrieval-augmented generation vector databases document processing and workflow automation. This role is especially important for building secure AI systems that can run locally or privately using company data without exposing sensitive information to public AI platforms.

The engineer will work closely with management sales technical teams and operations to convert business knowledge documents processes and customer data into usable AI agents and internal productivity tools.

Design and build AI agents for internal and customer use cases such as:

• Sales assistant agent
  
• Technical presales assistant
  
• Proposal and BoQ generation assistant
  
• ISO 9001 / compliance assistant
  
• Customer support knowledge agent
  
• Project documentation assistant
  
• Network and cybersecurity advisory assistant
  
• CRM and operations automation agents
  

Build AI workflows that can connect with internal systems such as:

• Zoho One / Zoho CRM
  
• Email
  
• Document repositories
  
• Helpdesk systems
  
• Project management tools
  
• Knowledge bases
  
• Internal databases
  

Develop agents that can perform tasks such as document search summarization classification recommendation data extraction report generation and workflow triggering.

Implement AI models and applications that can run in private or local environments including:

• On-premises servers
  
• Private cloud
  
• Local workstations
  
• Secure customer environments
  

Evaluate deploy and optimize open-source LLMs such as:

• Llama
  
• Mistral
  
• Qwen
  
• Gemma
  
• DeepSeek
  
• Other suitable open-source models
  

Work with local AI tools and frameworks such as:

• Ollama
  
• LM Studio
  
• vLLM
  
• Hugging Face
  
• LangChain
  
• LlamaIndex
  
• AutoGen / CrewAI or similar agent frameworks
  

Ensure AI systems are secure scalable reliable and aligned with company data privacy requirements.

Create clean structure and maintain private datasets from company documents including:

• Sales scripts
  
• Technical proposals
  
• Vendor datasheets
  
• BoQs
  
• Project documents
  
• SOPs
  
• ISO documents
  
• Customer support history
  
• CRM records
  
• Network and cybersecurity solution documents
  

Build and maintain searchable knowledge bases using:

• Embeddings
  
• Vector databases
  
• Retrieval-augmented generation
  
• Metadata tagging
  
• Document chunking
  
• Data classification
  
• Access controls
  

Work with vector databases such as:

• ChromaDB
  
• Qdrant
  
• Pinecone
  
• Weaviate
  
• FAISS
  
• PostgreSQL with pgvector
  

Develop user-friendly AI tools dashboards and internal applications using technologies such as:

• Python
  
• FastAPI
  
• Streamlit
  
• React /
  
• 
  
• REST APIs
  
• Docker
  

Build integrations with third-party systems through APIs webhooks and automation platforms.

Create proof-of-concepts and convert successful prototypes into production-ready tools.

Ensure company and customer data is handled securely.

Implement controls for:

• Data privacy
  
• User access
  
• Audit trails
  
• Prompt logging
  
• Model output validation
  
• Hallucination reduction
  
• Secure API usage
  
• Local/private model deployment
  
• Backup and version control
  

Help define internal standards for using AI safely across the company.

The candidate should have:

• Bachelors degree in Computer Science Software Engineering Data Science AI or related field.
  
• 2 years of experience in AI machine learning data engineering or software development.
  
• Strong Python programming skills.
  
• Practical experience with LLMs and AI application development.
  
• Experience with APIs databases and automation workflows.
  
• Experience building RAG systems or document-based AI search.
  
• Good understanding of embeddings vector databases and prompt engineering.
  
• Ability to work with unstructured documents such as PDFs Word files Excel sheets emails and knowledge base articles.
  
• Ability to turn business requirements into working AI solutions.
  
• Good documentation and communication skills.
  

Strong candidates will also have experience with:

• Local LLM deployment
  
• Cybersecurity or IT infrastructure knowledge
  
• Zoho CRM / Zoho One integrations
  
• Microsoft 365 / Google Workspace integrations
  
• Docker and Linux environments
  
• Cloud platforms such as AWS Azure or Google Cloud
  
• Fine-tuning or model optimization
  
• OCR and document intelligence
  
• Arabic and English language AI processing
  
• Building AI agents for sales presales support or operations
  
• Working in system integrator MSP cybersecurity or IT services environments
  

• Python
  
• LLMs
  
• Prompt engineering
  
• RAG
  
• Vector databases
  
• APIs
  
• Git
  
• SQL or NoSQL databases
  
• Document processing
  
• Basic cloud or server deployment
  

• LangChain
  
• LlamaIndex
  
• Ollama
  
• Hugging Face
  
• FastAPI
  
• Streamlit
  
• Docker
  
• Qdrant / ChromaDB / pgvector
  
• Zoho APIs
  
• Microsoft Graph API
  
• Arabic NLP
  
• Model fine-tunin