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AI / LLM Application Engineer

Tandem Interim
Dubai, UAE
Contract
Mid-Senior
Onsite
Discovered 5 days ago
Production software engineeringPythonTypeScriptAI/LLM application developmentRetrieval-augmented generation (RAG)Content ingestion and chunking
Free

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Production software engineeringPythonTypeScript
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About the Role

Build governed AI features for an existing internal client-relationship and business-development platform.

The solution will support AI-assisted summaries, next-best-action suggestions, and drafted communications grounded in approved data.

The build is controlled and compliance-conscious for a regulated business environment.

What You’ll Build

  • Implement RAG-based retrieval over approved internal content with source citations, freshness flags, and missing-data warnings.
  • Generate account summaries, meeting-preparation briefs, and draft follow-up communications.
  • Require human approval before any AI-generated communication is sent.
  • Implement versioning, audit logging, and evaluation and testing processes to detect quality regressions.
  • Support Arabic-language generation and translation.
  • Deploy the solution on private or client-controlled infrastructure rather than standard cloud AI APIs.

Must-Haves

  • At least four years of production software engineering experience using Python and/or TypeScript.
  • At least 18 months of experience building AI/LLM features used by real users, not only demos or side projects.
  • Hands-on experience with RAG ingestion, chunking, embeddings, retrieval, and source citation.
  • Experience evaluating AI output quality without a large labeled dataset.
  • Experience with authentication, access control, logging, and human-approval workflows for sensitive data.
  • Experience deploying AI systems on private or self-hosted infrastructure.

Nice-to-Haves

  • Experience with Arabic-language AI or right-to-left text handling is desirable.
  • Experience in banking, wealth or asset management, or another regulated industry is desirable.

Out of Scope

The solution will not autonomously send external communications or provide external client-facing AI.

Public cloud AI services such as Azure OpenAI will not be used; client data remains on approved infrastructure.

Training or fine-tuning an AI model from scratch is out of scope.

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