Forward Deployed Engineer

Plum · Афины, Греция · опубликовано 10 августа

ПрограммированиеPythonJavaScriptDocker

Millions of people want to grow their money but don't know where to start. More than 90% of adults don’t access traditional financial advice. That's the gap Plum was built to close.

We're building the proactive money platform that makes it easy for people to smartly and sustainably grow their money. Whether you're stashing the cash for tea and toast in your first home or catching some rays during retirement, we've got your back.

Since 2016, millions of people across 10 European markets have set aside more than £10 billion with Plum. But what we're most excited about is what comes next and the opportunity for our people to help shape it.

We're now going after something even bigger: the £2 trillion+ advised market in the UK and beyond, currently locked behind high fees and complexity. By combining AI-driven financial guidance with the products people actually need, we're building a solution for everyone, not just the wealthy few.

At Plum, you'll be part of a team that's ambitious, curious and driven. We move fast, learn from what doesn't work, challenge the status quo and, most importantly, build something that makes people's lives better. We believe great ideas can come from anywhere, and that the best work happens when people feel trusted to take ownership, collaborate openly and bring their whole selves to work.

Join nearly 300 Plumsters and be part of a team shaping the future of money

О роли

We are looking for a Forward Deployed Engineer to bridge our Engineering and Customer Operations teams. You'll bring engineering discipline into operations and operational reality back into product, with a seat at the table in both.

You'll work with high autonomy across Customer Support, Fincrime, and Wealth Ops, embedded with each team rather than waiting for requirements from a central function. Using Python, JS, AI tools like Claude and Gemini, and automation platforms like Zapier & Intercom workflows,, you'll turn operational pain points into production-grade solutions and feed field insights back to Product and Engineering so that one-off wins become platform capability.

Обязанности

Embed with operational teams to scope where AI and automation reduce manual effort, inconsistency, or friction. Prototype fast, validate before committing, then harden into production-grade solutions.
Write and maintain Python services, automation scripts, and API integrations that operate reliably in production. Not one-off scripts, but code you own, monitor, and improve continuously.
Own the KPIs your solutions affect: automation rate, CSAT, containment, processing time. Treat every AI agent and automation as a product you run, not a project you hand off.
Own the full lifecycle of AI agents in production: procedures, prompt engineering, escalation logic, routing, performance monitoring, and continuous improvement through AI-assisted QA.
Design, configure, and iterate on automation pipelines (Zapier) and AI workflows (Claude, Gemini, and others as the stack evolves). Translate operational problems into working systems without dependency on Engineering, but know when to pull them in.
Feed technical insights from the field back to Product and Engineering. Identify where custom work should become product capability. Participate in engineering reviews when your domain is involved.

Ideal you

Production engineering experience: you've shipped and maintained code in production not just notebooks or scripts. Python is our preferred language and what you'll work in day-to-day, but we care more about solid fundamentals and a track record of real-world delivery than the specific language on your CV.
Hands-on AI/LLM experience: prompt engineering, chaining workflows, building evaluations, and iterating on outputs in production, not just demos. Experience with agent frameworks (Google ADK, LangChain, or similar) is a strong plus.
Engineering fundamentals: you write clean, readable, maintainable code. You understand the full application lifecycle request/response cycles, sync vs. async patterns, how services communicate, and how code gets from a commit to production (CI/CD). You know when to reach for a proper service vs. a script.
Customer fluency: you can understand a non-technical team lead's real problem and translate it into a technical plan they trust. Strong written communication for documentation and AI instructions.
Radical ownership: when something breaks in production or an AI agent underperforms, you diagnose, fix, and strengthen the system so the same failure doesn't recur.
Frontend low-code adaptability: willing and able to pick up low-code platforms (e.g. Appsmith, Retool) to build and extend internal tools. You don't need to be a frontend engineer, but you're comfortable with JavaScript fundamentals and can learn a new tool quickly to ship something an ops team can actually use.
Comfort with ambiguity: you scope, prioritise, and deliver without waiting for someone to write you a spec.
Regulated environment awareness is a strong plus. Experience in financial services or FCA-adjacent environments preferred.