Staff AI Engineer

Responsibilities

Architect and design core AI platform components including model orchestration, RAG, and agentic workflows to power personalized financial guidance. Lead the end-to-end development of LLM-powered customer experiences while ensuring safety, accuracy, and regulatory compliance.

Requirements

Requires a proven track record of technical leadership in designing and operating LLM-powered systems at scale. Strong software engineering fundamentals in Python, distributed systems, and cloud infrastructure are essential.

Skills

• AI Engineering
• LLM
• Python
• RAG
• Agentic systems
• Distributed systems
• Cloud infrastructure
• Model orchestration
• Prompt engineering
• System design
• Observability
• Technical leadership
• API
• Data science
• Financial infrastructure

Benefits

• Stock options
• Private health insurance
• Annual training budget
• Plum Max subscription
• Referral scheme
• Flexible remote working
• Team breakfasts
• Team lunches
• 25 days holiday
• 45 work-from-anywhere days
• Sabbatical
• Enhanced parental leave
• Wedding allowance
• Paid volunteering day
• Annual team trip

About this role

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
The Role
At Plum, we’re looking for engineers who care deeply about technology, customer impact, and building things that scale.
We’re looking for a Staff AI Engineer to work across our AI Platform and Wealth Advisor teams, the teams behind the intelligence that powers Plum. The AI Platform team builds the foundations (model orchestration, retrieval, evaluation and guardrails) that every AI experience at Plum runs on, while the Wealth Advisor team uses those foundations to deliver trusted, personalised financial guidance to millions of customers. Together, they tackle some of Plum’s most important and technically interesting challenges: making AI-driven financial advice safe, accurate and accessible to everyone.
You’ll help shape the technical direction of AI at Plum, connecting LLM-powered products, backend systems, and financial infrastructure to create a platform that’s reliable, scalable, and built for rapid innovation.
What You Will Do
Architect and design the core components of our AI platform, from model orchestration to retrieval (RAG), agentic workflows, prompt and context management, so that AI capabilities can be built once and adopted across every Plum team
Lead the end-to-end development of LLM-powered customer experiences for the Wealth Advisor, from system design and tool integration through deployment, monitoring and iteration in production
Build rigorous evaluation systems including golden datasets, LLM-as-judge grading, regression gates on prompt/model changes and offline-to-online metric correlation, so we can ship AI improvements quickly with confidence
Design the guardrails, safety and observability layers (tracing, cost and latency monitoring, content and action controls) that make AI-driven financial guidance trustworthy in a regulated environment
Drive the AI Strategic Vision and roadmap, evaluating emerging models, tools and techniques and ensuring our architecture supports high-volume experimentation, rapid iteration and future business needs
Promote Continuous Improvement by driving architectural standards, engineering best practices, and operational excellence for AI systems across multiple teams
Provide guidance to and mentor Senior Engineers and other team members, raising the bar on AI engineering craft and fostering a culture of technical excellence and career growth
Identify root causes of systemic issues, from model quality regressions to architectural bottlenecks, determining short-term mitigations and long-term strategic resolutions
Partner closely with Staff Engineers, Product Managers, Data Scientists and Compliance to design AI solutions that unlock new growth opportunities while meeting the standards expected of a regulated financial product
What We Look For
Proven track record of technical leadership, with experience designing, shipping and operating LLM-powered systems in production at scale
Hands-on experience across the modern AI stack: agentic systems (tool use, orchestration, multi-step planning), RAG and retrieval pipelines, prompt engineering, and fine-tuning where it adds value
Rigour in evaluation methodology: you know how to measure whether an AI system is actually good, design evals that catch regressions, and make the data-backed “don’t ship” call when needed
Strong software engineering fundamentals: Python, distributed systems, APIs, cloud infrastructure, that you have used over the years to build AI products on solid foundations
High level of pragmatism; you understand when to build for scale and when to optimise for speed of learning, and you balance model capability against cost, latency and reliability
Strong planning and prioritisation skills, with the ability to translate high-level business goals into actionable technical strategies across the AI stack
Ability to share product insight with stakeholders, challenge product decisions with data, and act as a bridge between Engineering, Product, and Data Science
Demonstrated capacity to clearly and concisely communicate about complex technical, architectural, and/or organisational challenges to both technical and non-technical executives
Experience working within a cross-functional team and collaborative environment; ability to facilitate technical decision-making and resolve conflicts across teams
Self-motivated and self-managing, with excellent organisational skills and a focus on high-leverage work
An appreciation for the responsibility that comes with applying AI to people’s money. Awareness of safety, fairness and regulatory considerations is a strong plus
Plum Perks
We're all in this together!...

About Plum Fintech

Financial Services · 201-500 employees · headquartered in London, England · founded 2016