Senior AI Engineer (up to £140k)

Dex; Greater London; Sur place; GBP 120 000 - 180 000; Plein temps

Résumé du poste

Dex partners with a Series A fintech startup to build native, agentic infrastructure for high-stakes private equity diligence. You will join as a Senior AI Engineer owning the core harness from execution internals to retrieval pipelines and evaluators.

This role emphasizes streaming graph execution, interruptible tool calls, and robust, cited analysis through multimodal document search. You will collaborate with founders and private equity domain experts to turn complex diligence workflows into

Qualifications

• 5+ years building and scaling production backend services with AI-powered systems.
• Proven track record bringing LLM features, agents, or complex retrieval systems to production with eval results.
• Deep expertise in Python and production search/data infra such as OpenSearch, PostgreSQL, FastAPI

Responsabilités

• Design, ship, and scale autonomous agents that research companies, digest complex financial documents, and generate verifiable, cited analysis.
• Build proprietary foundation infrastructure, including a streaming-first graph execution framework and an interruptible, resumable code execution environment for tool use.
• Develop multimodal retrieval pipelines combining vision-language models for OCR, deep document search, and end-to-end claim attribution.
• Engineer production eval suites and feedback loops that serve as the definitive gate for whether harness modifications and model updates actually improve output quality.
• Collaborate closely with founders and private equity domain experts to turn complex, high-stakes diligence workflows into reliable programmatic systems.

Connaissances

Python

OpenSearch

PostgreSQL

FastAPI

Distributed queues

Outils

OpenAI API

LLM tooling

Description du poste

This role is with one of Dex's trusted partner companies. We work closely with their teams to truly understand their culture, goals, and what they're looking for, so we can match you with the right opportunity and give you context about the role before you commit to a process.

The role

Most AI tools in finance are brittle prompt wrappers over generic models. This Series A startup builds native agentic infrastructure for multi-billion-dollar private equity funds, automating technical sourcing, diligence, and portfolio analysis with fully cited audit trails. Backed by top fintech and venture investors and growing revenue more than ten-fold over the past year, they have achieved clear product-market fit with top-tier buyout and growth equity deal teams across the US and Europe.

You will join as a Senior AI Engineer owning the core agent harness end to end, from execution internals and retrieval pipelines to the evals that prove system reliability. This role is not about stitching together off-the-shelf framework templates or tweaking demos for show. It is about engineering streaming graph execution, interruptible tool calling, and multimodal document search robust enough that investment committees trust it with nine- and ten-figure decisions.

The work

• Design, ship, and scale autonomous agents that research companies, digest complex financial documents, and generate verifiable, cited analysis.
• Build proprietary foundation infrastructure instead of relying on generic wrappers, including a streaming-first graph execution framework and an interruptible, resumable code execution environment for tool use.
• Develop multimodal retrieval pipelines combining vision-language models for OCR, deep document search, and end-to-end claim attribution.
• Engineer production eval suites and feedback loops that serve as the definitive gate for whether harness modifications and model updates actually improve output quality.
• Collaborate closely with founders and private equity domain experts to turn complex, high-stakes diligence workflows into reliable programmatic systems.

What You Bring

• 5+ years building and scaling production backend services at a venture-backed startup or top-tier tech company, with full ownership of AI-powered systems.
• Proven track record taking LLM features, agents, or complex retrieval systems to production, with eval results and operational war stories to prove it.
• Deep expertise in Python and production search/data infrastructure such as OpenSearch, PostgreSQL, FastAPI, and distributed message queues.
• An eval-driven mindset that treats benchmarking, grounded verification, and error analysis as core engineering responsibilities, not an afterthought.