At a Glance
- Tasks: Build and ship AI-powered software in a dynamic, data-rich environment.
- Company: Join InvestCloud, a leader in wealth technology transforming the financial industry.
- Benefits: Enjoy competitive salary, hybrid work, generous holiday, and excellent health benefits.
- Other info: Collaborative culture with opportunities for growth across various engineering domains.
- Why this job: Tackle real engineering challenges while using cutting-edge AI tools to make an impact.
- Qualifications: 5+ years in software engineering with experience in complex systems and AI tooling.
The predicted salary is between 70000 - 90000 € per year.
InvestCloud is a private-equity backed platform business supporting over $6 trillion of assets globally, with deep, long-standing relationships across the asset and wealth management ecosystem. Private markets are rapidly becoming a core part of wealth portfolios – but the industry infrastructure has not kept pace. Most wealth managers still rely on manual processes, fragmented data, and operational workarounds to deliver private market exposure. InvestCloud’s Private Markets Network (PMN) is designed to change that. PMN is a network-level execution and processing platform that enables private market investments to be delivered at managed-account scale, with the same operational discipline and integration model that wealth managers expect in public markets.
This is a senior engineering hire into the PMN team. You will contribute to the build-out of PMN and the broader InvestCloud platform – shipping production software across a complex, data-rich environment, and bringing modern AI tooling to bear wherever it makes the team and the platform more effective.
Purpose of the Role
We are looking for a strong software engineer – someone who has spent their career building and shipping production software in complex environments, and who treats modern AI tooling as a natural part of their engineering toolkit. The role spans platform engineering and internal tooling. On the platform side, you will be embedded in PMN, working alongside product and engineering peers to build out core capabilities across PMN, core platform, and value-added services. On the internal tooling side, you will build AI-powered applications that make the business smarter and faster – from operational automation to intelligent internal tools that help teams work better. In both cases, the expectation is the same: well-built, production-grade software that the people around you can depend on.
What You’ll Actually Be Doing
- Building and shipping platform features across PMN, core platform, or VAS – working from a well-defined brief and owning your delivery end-to-end.
- Integrating new capabilities into existing services and infrastructure, safely and consistently with the platform’s architecture.
- Building internal tools that use AI to solve real business problems – things like intelligent assistants, workflow automation, or operational dashboards that connect to live business data.
- Writing clean, well-tested, well-documented code that your peers can build on and maintain.
- Debugging, improving, and taking ownership of live systems – reliability and observability included.
- Contributing to technical design and architecture discussions within the team.
- Collaborating with the Product & Prototyping Lead to take validated concepts through to production quality.
Key Responsibilities
Core Network Engineering
- Contribute to the build-out of PMN and the broader InvestCloud platform – delivering features and capabilities that are production-ready, well-integrated, and maintainable.
- Work within a complex, evolving codebase; understand how the pieces fit together and build in a way that is consistent with the platform’s architecture and standards.
- Integrate with existing services, data sources, and infrastructure across the InvestCloud ecosystem.
- Work with core platform and VAS engineering teams as your remit expands beyond PMN.
Internal Tooling
- Design and build AI-powered internal tools that solve real problems for the business, for example: Intelligent assistants that surface information or automate repetitive tasks for operational teams.
- Workflow automation that removes manual steps from internal processes.
- Internal applications that connect to business data and make it more accessible and actionable.
- Apply modern AI tooling – LLMs, retrieval pipelines, orchestration frameworks – where it genuinely improves the outcome; use conventional engineering where it doesn’t.
Production Standards
- Ship software that is reliable, observable, and maintainable – monitoring, logging, and error handling are part of the job, not an afterthought.
- Write code and documentation to a standard that the team can build on and support without you in the room.
- Contribute to code review, testing practices, and shared engineering standards.
Collaboration
- Work closely with the Product & Prototyping Lead to understand what has been validated and needs to be built.
- Engage with PMN Ops and product stakeholders to understand the systems and data you are building against.
- Share knowledge and contribute to the team’s collective understanding of modern tooling and engineering patterns.
Key Stakeholders
- PMN Engineering Leadership
- Product & Prototyping Lead
- PMN Operations
- InvestCloud Core Platform Engineering
- Value-Added Services (VAS) Engineering Teams
- Internal business stakeholders (for internal tooling)
Essential Skills & Experience
- Strong software engineering background – typically 5+ years building and shipping production software.
- Proficient in one or more modern backend languages; comfortable across the typical stack including cloud infrastructure, relational databases, APIs, and web frameworks.
- Experienced at working within complex, integrated platform codebases – not just greenfield projects.
- Demonstrated track record of shipping production software that uses LLMs and associated techniques – not just prototypes or internal experiments.
- This includes: Retrieval-Augmented Generation (RAG) – document indexing, retrieval pipelines, grounding, and evaluation.
- Agentic patterns and orchestration frameworks – multi-step workflows, tool use, evaluation loops.
- Model Context Protocol (MCP) and similar integration patterns for connecting LLMs to real data and services.
- Prompt design, model evaluation, and the practical trade-offs of LLM systems in production.
- Strong fundamentals: clean code, testing, documentation, observability, and operational reliability.
- Collaborative and comfortable working from well-defined problems alongside product and engineering peers.
Desirable Skills & Experience
- Experience in financial services, B2B SaaS, or other regulated or data-sensitive environments.
- Exposure to private markets, wealth platforms, or operations tooling.
- Experience building internal tooling or operational automation for business teams.
- Familiarity with data pipelines, event-driven architecture, or operational systems integration.
- Experience contributing to shared platform or infrastructure codebases.
Personal Attributes
- Takes pride in the quality and reliability of what they ship.
- Pragmatic – gets things done without over-engineering, but doesn’t cut corners on what matters.
- Curious about how modern tooling – including AI – is evolving, and grounded in what actually works in production.
- Collaborative and straightforward – works well across product, ops, and engineering without friction.
- Comfortable in a fast-moving environment where the problems are real and the delivery bar is high.
Why This Role Is Different
- A serious engineering challenge – complex systems, real data, and problems that matter to the business.
- Unusually broad scope: platform engineering and internal tooling in the same role, at the same standard.
- The chance to apply modern AI tooling to real problems – not as a pilot, but as part of how the team builds.
- A natural growth path across core platform and VAS as your contribution expands.
About InvestCloud
InvestCloud, a global leader in wealth technology, aspires to enable a smarter financial future. Driving the digital transformation of the wealth management industry, the company serves a broad array of clients globally, including Wealth and Asset Managers, Wirehouses, Banks, RIAs, and Insurers. In terms of scale, the company’s clients represent more than 40 percent of the $132 trillion of total assets globally. As a leader in delivering personalization and scale across advisory programs, including unified managed accounts (UMA) and separately managed accounts (SMA), the company is committed to the success of its clients. By equipping and enabling advisors and their clients with connected technology, enhanced intelligence, and inspired experiences, InvestCloud delivers leading digital wealth management and financial planning solutions, complemented by a dynamic data warehouse, which scale across the complete wealth continuum. In 2024, InvestCloud was named CNBC World’s Top Fintech Company, a proof point of the company’s commitment to innovation and client success. Headquartered in the United States, InvestCloud serves clients around the world.
Our Values
- Client Connected
- Human Centered
- Technology Forward
- Respect + Integrity
- Excellence
Compensation & Benefits
- Competitive base salary
- Discretionary bonus
- Excellent pension, private medical, life assurance
- Hybrid working model
- 28 days holiday plus bank holidays
The actual salary will vary based on the applicant’s education, experience, skills, and abilities, as well as internal equity and alignment with market data. The salary may also be adjusted based on the applicant’s geographic location.
Senior AI Software Engineer in London employer: InvestCloud Careers
InvestCloud is an exceptional employer, offering a dynamic work culture that fosters innovation and collaboration in the rapidly evolving wealth management sector. With a commitment to employee growth, you will have the opportunity to tackle complex engineering challenges while leveraging modern AI tools, all within a supportive hybrid working environment. Enjoy competitive compensation, generous benefits, and the chance to make a meaningful impact on the future of financial technology.
StudySmarter Expert Advice🤫
We think this is how you could land Senior AI Software Engineer in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those at InvestCloud. A friendly chat can open doors that a CV just can't.
✨Tip Number 2
Show off your skills! If you’ve got a portfolio or GitHub with projects that highlight your AI and software engineering chops, make sure to share it during interviews.
✨Tip Number 3
Prepare for technical interviews by brushing up on your coding skills and understanding of AI tooling. Practice common algorithms and system design questions to impress the hiring team.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people at InvestCloud.
We think you need these skills to ace Senior AI Software Engineer in London
Some tips for your application 🫡
Tailor Your Application:Make sure to customise your CV and cover letter to highlight your experience with production software and AI tooling. We want to see how your skills align with the role, so don’t hold back on showcasing relevant projects!
Showcase Your Problem-Solving Skills:In your application, share examples of how you've tackled complex engineering challenges in the past. We love seeing candidates who can demonstrate their ability to build reliable and maintainable software in a fast-paced environment.
Be Clear and Concise:When writing your application, keep it straightforward and to the point. Use clear language to describe your experiences and achievements, as this will help us quickly understand your fit for the role.
Apply Through Our Website:We encourage you to submit your application directly through our website. This way, you’ll ensure it reaches the right people and gets the attention it deserves. Plus, it’s super easy!
How to prepare for a job interview at InvestCloud Careers
✨Know Your Stuff
Make sure you brush up on your software engineering fundamentals, especially around production software and AI tooling. Be ready to discuss your experience with complex codebases and how you've integrated modern AI techniques into your projects.
✨Showcase Your Problem-Solving Skills
Prepare examples of how you've tackled real business problems using AI-powered tools or operational automation. Highlight specific projects where your contributions made a significant impact, especially in financial services or data-sensitive environments.
✨Collaborate Like a Pro
Since this role involves working closely with product and engineering teams, be prepared to discuss how you've successfully collaborated in the past. Share experiences where you engaged with stakeholders to understand their needs and how you delivered solutions that met those requirements.
✨Ask Smart Questions
At the end of the interview, don’t shy away from asking insightful questions about the PMN team and InvestCloud's vision for the future. This shows your genuine interest in the role and helps you gauge if the company aligns with your career goals.