Member of Technical Staff - AI

Model ML

Greater London

On-site

GBP 90,000 - 130,000

Full time

9 days ago
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Benefits offered by this job

Equity
Challenging projects

Job summary

Model ML is seeking a senior software engineer to own large portions of AI agent infrastructure, including multi-agent systems, RAG pipelines, and evaluation frameworks. You will deliver AI-powered features into production at scale, ensuring performance, reliability, and security across the stack.

You will contribute across the stack—from frontend interfaces to backend APIs, databases, and deployment pipelines—while mentoring junior developers and upholding engineering best practices.

Qualifications

  • 5+ years of professional software engineering experience.
  • Hands-on experience building and deploying AI applications in production environments.
  • Strong backend development skills (Python preferred).
  • Solid understanding of relational databases.
  • Experience with Git and collaborative development workflows.
  • Knowledge of cloud infrastructure, containerization (Docker, Kubernetes), and CI/CD pipelines.
  • Experience implementing background workers and task queues (Celery, RQ, etc.).
  • Proficiency with Redis for caching, pub/sub, or job queues.
  • Hands-on experience building and deploying AI applications in production environments.
  • Experience implementing RAG pipelines, AI agent orchestration, and performance monitoring.
  • Familiarity with LLM evaluation techniques and tools for measuring model accuracy, reliability, and safety.

Responsibilities

  • Build, test, and deploy backend services and APIs (Python/ Django/ FastAPI preferred, but other languages/frameworks welcome).
  • Collaborate with founders, growth team, designers, and other engineers to deliver high-impact features.
  • Ensure scalability, performance, and security across the stack.
  • Develop and deploy AI-powered features in production, including RAG systems, multi-agent infrastructure, and evaluation frameworks (Evals).
  • Create data pipelines for AI model training, evaluation, and continuous improvement.
  • Mentor junior developers and promote engineering best practices.

Skills

Backend development
Python
Cloud
Docker
Kubernetes
CI/CD
Redis
Celery
RAG pipelines
LLM evaluation

Tools

Git
PostgreSQL
SQL
FastAPI
Django

Job description

Company Overview

Model ML is the AI workflow builder transforming how major financial institutions produce and validate client-ready work. Model ML converts complex, manual processes into fully automated AI systems that scale across global teams. In under a year, Model ML has become one of the fastest growing enterprise AI platforms worldwide and recently closed a $75 million Series A, one of the largest fintech Series A rounds ever. The round was backed by FT Partners, Y Combinator, LocalGlobe, QED, 13books, and other top global investors.

Job Description

In this role, you will own and drive large portions of our AI agent infrastructure, from designing and deploying multi-agent systems to integrating Retrieval-Augmented Generation (RAG) pipelines, and evaluation frameworks. You will be responsible for delivering AI-powered features into production at scale — ensuring they are performant, reliable, and secure — while also contributing across the stack, from frontend interfaces to backend APIs, databases, and deployment pipelines.

Responsibilities
  • Build, test, and deploy backend services and APIs (Python/ Django/ FastAPI preferred, but other languages/frameworks welcome).
  • Collaborate with founders, growth team, designers, and other engineers to deliver high-impact features.
  • Ensure scalability, performance, and security across the stack.
  • Develop and deploy AI-powered features in production, including RAG (Retrieval-Augmented Generation) systems, multi-agent infrastructure, and evaluation frameworks (Evals).
  • Create data pipelines for AI model training, evaluation, and continuous improvement.
  • Mentor junior developers and promote engineering best practices.
What You Can Expect
  • It won't be easy; in fact, it will be very hard.
  • BUT, it will be a lot of fun.
  • You need to be comfortable in being uncomfortable; timelines will change, priorities will most likely shift
  • Be prepared to sacrifice your work-life balance in exchange for joining an incredible journey and learning a lot along the way.
Requirements
  • 5+ years of professional software engineering experience.
  • Hands-on experience building and deploying AI applications in production environments.
  • Strong backend development skills (Python preferred)
  • Solid understanding of relational databases.
  • Experience with Git and collaborative development workflows.
  • Knowledge of cloud infrastructure, containerization (Docker, Kubernetes), and CI/CD pipelines.
  • Strong problem-solving skills and a passion for building great products.
  • Experience implementing background workers and task queues (Celery, RQ, etc.).
  • Proficiency with Redis for caching, pub/sub, or job queues.
  • Hands-on experience building and deploying AI applications in production environments.
  • Experience implementing RAG pipelines, AI agent orchestration, and performance monitoring.
  • Familiarity with LLM evaluation techniques and tools for measuring model accuracy, reliability, and safety.
What We Offer
  • You will be reporting directly to the founders, who have two successful venture-backed exits under their belt.
  • Competitive salary + equity
  • Supportive and innovative work environment
About The Interview

Our Process: We're very conscious of everyone's time, so we want to make the process as efficient as possible.

  • Call 1: 30-minute intro call with our Talent Acquisition team
  • Call 2: 30-minute technical screen
  • Call 3: 20-minute systems design deep-dive
  • Call 4: Onsite interview with Engineering Leadership
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