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 60000 - 80000 £ 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.
AI Software Engineer in London employer: InvestCloud Careers
InvestCloud is an exceptional employer, offering a dynamic work environment where innovation meets collaboration. With a strong focus on employee growth, the company provides opportunities to tackle complex engineering challenges while leveraging modern AI tools in a supportive hybrid working model. Employees enjoy competitive compensation, comprehensive benefits, and a culture that values client connection, respect, and excellence, making it an ideal place for those seeking meaningful and rewarding careers in the wealth technology sector.
StudySmarter Expert Advice🤫
We think this is how you could land AI Software Engineer in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with people on LinkedIn. You never know who might have the inside scoop on job openings or can put in a good word for you.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving AI tooling and complex systems. This will give potential employers a taste of what you can do and set you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your technical skills and understanding the company’s products. Be ready to discuss how you can contribute to their platform and internal tooling – they’ll love your enthusiasm!
✨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. Plus, it shows you’re genuinely interested in joining the InvestCloud team.
We think you need these skills to ace AI Software Engineer in London
Some tips for your application 🫡
Tailor Your Application:Make sure to customise your CV and cover letter for the AI Software Engineer role. Highlight your experience with production software and modern AI tooling, as these are key aspects of what we're looking for.
Showcase Your Projects:Include specific examples of projects you've worked on that demonstrate your skills in building reliable, maintainable software. We love seeing how you've tackled complex problems, especially if they relate to AI or financial services.
Keep It Clear and Concise:When writing your application, aim for clarity. Use straightforward language and avoid jargon where possible. We appreciate well-structured applications that get straight to the point!
Apply Through Our Website:Don't forget to submit your application through our website! This ensures it gets to the right people quickly and helps us keep track of all applicants efficiently.
How to prepare for a job interview at InvestCloud Careers
✨Know Your Tech Stack
Make sure you’re well-versed in the modern backend languages and technologies mentioned in the job description. Brush up on cloud infrastructure, relational databases, and APIs. Being able to discuss your experience with these tools will show that you’re ready to hit the ground running.
✨Showcase Your AI Experience
Since this role involves using AI tooling, be prepared to discuss specific projects where you've implemented LLMs or similar techniques. Highlight your understanding of concepts like Retrieval-Augmented Generation and orchestration frameworks, as this will demonstrate your capability to contribute effectively to the team.
✨Prepare for Problem-Solving Questions
Expect to face questions that assess your problem-solving skills, especially in complex environments. Think of examples from your past work where you’ve tackled challenging issues, particularly those involving operational automation or internal tooling. This will help you illustrate your pragmatic approach to engineering.
✨Emphasise Collaboration Skills
This role requires working closely with product and engineering teams, so be ready to discuss how you’ve successfully collaborated in the past. Share examples of how you’ve contributed to team discussions, code reviews, or design sessions, as this will highlight your ability to work well in a fast-paced environment.