Senior AI Platform Engineer - Agentic Workflows

Flow Engineering, Inc.; Greater London; Hybrid; GBP 90,000 - 140,000; Full time

Benefits offered by this job

Health, dental, and vision coverage

Flexible time off

Job summary

Flow Engineering is hiring software engineers to build AI-powered capabilities that help teams author, review, and manage requirements. You will work on agentic systems and domain engineer workflows, bringing AI into how teams reason about their systems.

This role sits at the intersection of AI, product, and full-stack engineering, taking ideas from prototype to production-ready features across the stack, with a focus on reliability, observability, and scalable infrastructure.

Qualifications

• 5+ years producing production software in cloud environments.
• Hands-on experience with modern LLM providers and tooling.
• Familiarity with prompt design and retrieval-augmented systems.
• Ability to compare models, architectures, and deployment patterns.
• Comfortable in a high-ownership, fast-paced environment.

Responsibilities

• Design and ship AI-powered features for drafting, checks, and intelligent suggestions.
• Build agentic workflows for engineers to explore designs, simulate changes, and validate requirements.
• Evaluate and integrate language models and tooling, balancing reliability, latency, and cost.
• Develop data pipelines, evaluation harnesses, prompt/model management, observability, and guardrails.
• Work across backend, APIs, and UI hooks to deliver complete AI features.
• Collaborate with product and customers to identify high-value workflows and iterate quickly.

Skills

Production software

LLM tooling

Prompt design

RAG patterns

Tradeoff analysis

Ownership

Tools

OpenAI

Anthropic

Hugging Face

Vector stores

Postgres

Job description

Flow Engineering is hiring software engineers to build AI-powered capabilities that help teams author, review, and manage requirements. You will work on agentic systems and domain engineer workflows, bringing AI into how teams reason about their systems.

This role sits at the intersection of AI, product, and full-stack engineering, taking ideas from prototype to production-ready features across the stack, with a focus on reliability, observability, and scalable infrastructure.