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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. Compensation Range: £80K - £180K
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.