EQL Global
Website:
eqlglobal.com
Job details:
AI Engineer | EQL Global
In financial research, a wrong number is worse than no number. EQL Global is hiring an AI Engineer to build the layer that turns our first-party data, which covers every listed company in Europe, into answers analysts can trust and trace back to the source.
About EQL Global
EQL is a compliance-first financial data and AI platform for European capital markets. We deliver filings, earnings call transcripts, press releases, financial actuals and estimates for more than 33,000 listed companies in 89 countries. We source our data first-hand, host everything in the EU and design the platform around MiFID II, DORA, GDPR and the EU AI Act.
Banks, asset managers and investment platforms use EQL through three surfaces: EQL Desktop, our analyst workspace; a REST/SSE API; and an MCP server, listed in Anthropic's and Replit's connector directories, that brings our data straight into the AI tools analysts already use.
- Own and improve retrieval across our corpus: hybrid search, reranking and source citation over filings, transcripts, press releases and fund letters in several European languages.
- Develop extraction pipelines that turn unstructured documents into structured, auditable data, from the financial tables in an interim report to what a fund manager writes about a single holding.
- Drive the development of our chat API, a ready-made research assistant delivered through one endpoint, with EQL carrying the data, modelling and inference behind it.
- Improve the transcription pipeline that brings earnings calls and recorded client meetings into the platform.
- Design the tools our MCP server exposes, so AI agents acting for analysts get precise, well-scoped access to our data.
- Build the evaluation framework that shows, in numbers, whether a change made answers better: reference datasets, accuracy regression tests and citation checks that run before anything ships.
- Select and run models with quality, cost, latency and data residency in mind, and document them well enough to hold up in a bank's due diligence.
What we're looking for
- A track record of shipping LLM-based systems that real users depend on, not just prototypes. You can walk us through a retrieval pipeline that failed, and how you found out.
- Strong Python and sound engineering habits: testing, code review, monitoring.
- Hands-on experience with embeddings, vector and hybrid search, chunking and reranking.
- Experience with messy documents: PDFs, tables, scanned reports, inconsistent formats.
- A rigorous approach to evaluation. You trust a test set more than a demo.
- Comfort with AWS and with owning what you deploy.
- Clear written English and the judgement to work independently in a small team.
Nice to have
- Background in capital markets, equity research or financial data. Knowing the difference between reported and adjusted EBIT helps here.
- Swedish, Norwegian, Danish or Finnish. Much of our Nordic source material, from press releases to fund letters, is written in the local language.
- Experience with MCP, tool use or agent frameworks.
- Speech-to-text or audio processing.
- AI work in a regulated industry such as finance, healthcare or the public sector.
What we offer
- Real ownership of how AI works in a product institutional investors rely on.
- A small team with short decision paths, working directly with the founders.
- Competitive salary and employee stock options.
- The chance to help build a European alternative in a category long dominated by US incumbents.
How to apply
Apply here on LinkedIn with your CV. In a few lines, tell us about an AI system you've shipped and how you knew it worked. We review applications on a rolling basis.
Click on Apply to know more.
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