Senior Software Engineer (AI)

Role Context

The company 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. The company’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 company 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

• Contribute to the build-out of PMN and the broader company 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 company ecosystem.
• Work with core platform and VAS engineering teams as your remit expands beyond PMN.

• 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.

• 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.

• 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
• Company 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.

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.