Software Engineer- London

The Engineering Company

Greater London

On-site

GBP 60,000 - 80,000

Full time

14 days+

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Benefits offered by this job

Competitive salary
Meaningful equity
Health, dental, and vision coverage
Flexible time off

Job summary

The Engineering Company is seeking experienced software engineers to develop AI-powered capabilities that enhance requirements management. The role involves designing and shipping innovative features, working with LLMs, and ensuring seamless integration across the stack from backend to UI. Candidates should have over 3 years of software development experience, particularly in cloud environments, and be comfortable in a fast-paced, ownership-driven culture. Competitive salary and flexible time off are included in the offer.

Qualifications

  • 3+ years developing production software including cloud services.
  • Hands-on experience with modern LLM tooling.
  • Experience with evaluation methods and tradeoff reasoning.

Responsibilities

  • Design and ship AI-powered features for requirement management.
  • Build agentic workflows for system and domain engineers.
  • Evaluate and integrate language models for production use.
  • Maintain surrounding infrastructure including data pipelines.
  • Work across the stack to deliver complete AI features.

Skills

Production software development
Familiarity with LLM providers
Cloud environment operations
Prompt design
Tradeoff reasoning

Tools

TypeScript
Node.js
Python
Postgres

Job description

About Flow

Flow Engineering is an AI-native requirements platform for modern engineering organizations, enabling hardware teams to collaborate with AI agents to design, validate, and evolve complex systems with speed and rigor.

About the role

Flow is seeking software engineers to build AI-powered capabilities that help teams author, review, and manage requirements more effectively. You will work on agentic systems engineer and agentic domain engineer workflows—bringing AI into the center of how teams reason about their systems.

This role sits at the intersection of AI, product, and full-stack engineering: you will take ideas from prototype all the way to stable, observable features in production.

What you’ll do
  • Design and ship AI-powered features such as assisted requirement drafting, consistency checks, impact analysis, and intelligent suggestions for systems and domain engineers.

  • Build agentic workflows that help “agentic systems engineers” and “agentic domain engineers” explore designs, simulate changes, and validate requirements.

  • Evaluate and integrate language models and related tooling, optimizing for reliability, latency, cost, and debuggability in production.

  • Build and maintain the surrounding infrastructure: data pipelines, evaluation harnesses, prompt and model management, observability, and safety/guardrails.

  • Work across the stack—from backend integrations and APIs to simple UI hooks—to deliver complete AI features, not just model endpoints.

  • Partner with product and customers to identify high-value workflows, run experiments, and iterate quickly based on usage.

About you
  • 3+ years developing production software, including designing, testing, and operating services at scale in a cloud environment.

  • Hands‑on experience with modern LLM providers and tooling (e.g., OpenAI, Anthropic, Hugging Face, vector stores, RAG patterns).

  • Familiarity with prompt design, retrieval‑augmented systems, evaluation methods, and safety/guardrail approaches.

  • Ability to reason about tradeoffs between different models, architectures, and deployment patterns and make pragmatic decisions.

  • Comfortable working in a high‑ownership, fast‑paced environment where experiments and iteration are the norm.

Our stack (AI-leaning)
  • TypeScript/Node.js and Python for AI and backend services.

  • Modern LLM APIs and orchestration libraries for building agentic workflows.

  • Postgres and other managed cloud services for data and state.

How we work & values
  • Speed over everything: prototype AI workflows quickly, then harden what works.

  • Own, downscope, ship, iterate: one clear owner per feature, from prototype to production.

  • Fundamentals done well: evaluation, observability, and safety are part of the first version, not an afterthought.

  • Competitive salary and meaningful equity.

  • Health, dental, and vision coverage.

  • Flexible time off and support for experimentation, learning, and staying current with the AI ecosystem.

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