Senior Backend Engineer (up to £140k)

Dex; Greater London; On-site; GBP 90,000 - 140,000; Full time

Job summary

Dex partners with a Series A startup to recruit a backend systems engineer who will own the core distributed infrastructure behind a high-scale agentic runtime and streaming pipelines.

You will work with Python, FastAPI, PostgreSQL, OpenSearch, and message brokers (Kafka/RabbitMQ) to build scalable backends with observable, deterministic behavior for production use.

Qualifications

• 5+ years building and operating distributed backend systems or data platforms at scale in a startup or tech company.
• Strong production expertise in Python, FastAPI, PostgreSQL, OpenSearch, and streaming or message brokers such as Kafka or RabbitMQ.
• Proven experience building with LLMs and agents and making them reliable, deterministic, and observable in production.
• Experience taking complex services from design to high-scale deployment and day-two operations.

Responsibilities

• Architect and scale a streaming-first graph execution framework powering autonomous multi-step agent reasoning in production.
• Build sandboxed code execution environments that can be paused, inspected, and resumed mid-run for tool calling.
• Scale multimodal ingestion and OCR pipelines feeding self-hosted search clusters across large filings and reports.
• Engineer verification engines and data models that provide deterministic end-to-end citations for AI insights.
• Own core backend services and asynchronous messaging pipelines end-to-end using Python, FastAPI, Postgres, OpenSearch, and RabbitMQ or Kafka.

Skills

Python

FastAPI

PostgreSQL

OpenSearch

Kafka

RabbitMQ

LLMs & agents

Tools

PostgreSQL

OpenSearch

Kafka

RabbitMQ

Job description

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. Dex is an AI recruiter agent that helps you run your job search. Tell Dex your stack, seniority, and what you want to build. We will manage your applications and surface other opportunities that are a fit.

The role

Most AI tooling for financial services is shallow RAG over pitch decks. This Series A startup is building the agentic operating system used by multi-billion-dollar private equity funds to source, underwrite, and monitor investments, scaling ARR 15x over the past twelve months. Backed by top-tier venture investors with $20M in total funding and teams in London and New York, they have achieved rare product-market fit in one of the most demanding, accuracy-critical domains in enterprise software. You will join a lean engineering team owning the core distributed infrastructure behind their agentic runtime, streaming execution, and large-scale document pipelines. This is a whole-systems backend seat, not a ticket queue or an API-wrapper role. You will make the architectural calls on resilient code execution harnesses, multimodal search, and real-time data flows, shipping them directly into production for institutional deal teams.

The work

• Architect and scale a streaming-first graph execution framework that powers autonomous multi-step agent reasoning in production.
• Build sandboxed code execution environments that can be paused, inspected, and resumed mid-run for stateful programmatic tool calling.
• Scale multimodal ingestion and VLM-driven OCR pipelines feeding self-hosted search clusters across high-volume institutional filings and financial reports.
• Engineer verification engines and data models that provide deterministic, end-to-end citations for every AI-generated insight.
• Own core backend services and asynchronous messaging pipelines end-to-end using Python, FastAPI, Postgres, OpenSearch, and RabbitMQ or Kafka.

What You Bring

• 5+ years building and operating distributed backend systems or data platforms at scale within a venture-backed startup or top-tier tech company.
• Deep production expertise in Python, FastAPI, PostgreSQL, search clusters like OpenSearch, and streaming or message brokers such as Kafka or RabbitMQ.
• Proven experience building with LLMs and agents, with a clear grasp of what it takes to make them reliable, deterministic, and observable in production.
• Track record of taking complex services from initial architectural design through to high-scale deployment and day-two operations.

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