Senior LLM Engineer (Applied Research)

About Us

At IdeaSouq, we are building the "AI operating system" to transform how private market investors and funds discover, evaluate, and manage their opportunities.

Traditional investment workflows are drowning in data silos, manual screening, and overwhelming deal flow. We're a startup building the solution : an AI analyst that turns this deal flow chaos into funding intelligence. Our platform provides smart sourcing, deep evaluation based on a fund's unique thesis, agentic workflows to find missing data, and seamless portfolio monitoring, all while built on a foundation of enterprise-grade security and data sovereignty.

We are looking for a foundational engineer to join our small, high-impact team. If you are passionate about building secure, scalable, and self-evolving AI systems from the ground up, this is your opportunity to define the future of investment technology.

The Role

As our Senior LLM Engineer, you are the engine behind our "AI analyst." You will bridge the critical gap between abstract "state-of-the-art" LLM research and the concrete, production-grade data engineering required to make it work at scale.

You will be responsible for building the entire data and model lifecycle that allows our system to ingest, understand, and reason over vast, unstructured datasets (pitch decks, financial reports, transcripts, web data).

You are the kind of person who reads a new paper on agentic RAG on Monday, designs the data pipeline for it on Tuesday, builds the prototype by Thursday, and works with our cloud team to get it into production. This is not a pure research role; it is a hands-on "builder" role for someone who scans arXiv but builds for enterprise-scale, secure deployment.

Core Responsibilities

Data Engineering for AI

• Data Pipelines : Design, build, scale ingestion pipelines (unstructured / structured data).
• Vector DBs : Architect, manage, optimize vector stores (Milvus, Pinecone, AI Search).
• ETL / ELT for AI : Build cleansing workflows; turn "deal flow chaos" into model-ready data.
• Institutional Memory : Engineer data systems for continuous AI learning & versioning.

Applied LLM Research & Implementation

Key Qualifications & Skills

We are looking for a senior-level candidate with a proven track record of building data-intensive AI products.

Required Experience :

Technical Skillset :

Preferred Qualifications