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Salary
$127k – $167k per year
Location
Hybrid (London, United Kingdom)
Seniority
Senior

Confirmed on the employer's own hiring board on Oct 22, 2026. First seen by Alion on Oct 21, 2026. CAIS scores B on the Alion truth index.

Overview
Company
Impact
Profile match
CAIS is a New York financial technology company founded in 2009 that connects independent wealth advisers to alternative investments. Its platform handles fund access, education and operational workflow for private equity, credit and hedge fund allocations. The company serves thousands of advisory firms in the United States.
Backed by Motive Partners

About CAIS

CAIS is the pioneer in democratizing access to and education about alternative investments for independent financial advisors, empowering them to engage and transact with leading asset managers on a massive scale through a wide variety of alternative investment products and technology solutions. CAIS provides financial advisors with a broad selection of alternative investment strategies, including hedge funds, private equity, private credit, real estate, digital assets, and structured notes. CAIS also delivers industry-leading technology, operational efficiency, and world-class client service throughout the pre-trade, trade, and post-trade experience. CAIS serves over 2,500 wealth management firms that support more than 65,000 financial advisors who oversee approximately $8.5 trillion in end-client assets. 

About the role

We’re looking for a Senior Backend Product Engineer to join our Capital Markets technology team in London. This is a hybrid, hands-on role: you’ll design, build and run systems across Pre-Trade, Trade and Post-Trade, covering Structured Investments, Equity IPOs, Hedging & Monetization, ETFs, and more. 

We put a lot of emphasis on the “product” in product engineer. You’ll work alongside product managers and directly with the business to turn open-ended problems into working software, and the results show up in how a fast-growing company performs. AI is a big part of how we work: the team uses it throughout the development lifecycle and has already shipped several agentic features. You’ll help build the next ones. 

We work in small, autonomous teams using the Kanbanprinciples of optimizingflowandlimiting WIP. Theteam owns its work together, from shaping the problem through to running it in production.We collaborate closely with colleagues and stakeholders in New York. Engineers own their work from shaping the problem through to running it in production.While we have access to QA expertise, we consider quality to be everyone’s responsibility, so engineers own testing too. We care about strong engineering fundamentals, especially as AI changes how we build. 

You’ll mostly write Kotlin, working with Spring, Postgres, Elasticsearch and Kafka, and deploying to Kubernetes on AWS through GitHub and ArgoCD. 

Why join us 

  • Real ownership: you’ll shape problems with the business, not just pick up tickets 
  • Visible impact: your work shows up directly in how a fast-growing business performs 
  • Interesting domain: complex, real-world problems across the full trade lifecycle 
  • Engineering quality: strong fundamentals and high standards 
  • Modern codebase: we’ve moved off legacy, and our systems have been built in the last few years 

Skills & Experience  

  • Experience working as a software developer with Java or Kotlin server-side applications 
  • Track record of turning business problems into working software, with a clear, measurable impact 
  • Experience building and running mission-critical services in production, from CI/CD through to monitoring, alerting and incident response 
  • Strong testing habits across unit, integration and end-to-end tests, with good judgment about what to test at each level
  • Strong experience with Spring (Boot, Data, Security), relational database design, REST API design, and Kafka or a similar event streaming platform 
  • Experience working AI-first: using AI agents to build software, with an understanding of how LLMs work and good judgement about when to trust their output 
  • Technical leadership within your team, including mentoring less experienced engineers and setting and sharing engineering standards 
  • Clear communication, including explaining technical decisions to non-engineers 

Nice to have  

  • Financial services experience, ideally capital markets 
  • Elasticsearch, Kubernetes, Postgres, AWS, Terraform 
  • TypeScript and React, and/or motivation to try full stack development 
  • Experience building AI or agentic applications 

This role is a hybrid role, with at least 2-3 days spent out of our Old Street office - N1 7LB. 

CAIS is consistently recognized as a Best Place to Work, and our culture is at the heart of our success. We are committed to fostering an inclusive environment where employees can be their most authentic self and feel inspired and supported to bring their voice forward to drive community, growth, and innovation. We are an equal opportunity employer, and do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law.  Learn more about our culture, benefits, and people at https://www.caisgroup.com/our-company/careers. 

CAIS’ compensation package includes a market competitive salary, a performance bonus, and exceptional benefits. If you are located in London, England, the base salary range for this role is £95,000 - £125,000. Actual compensation is influenced by a wide array of factors including but not limited to skill set, level of experience, and specific office location.  

We use technology, including AI tools, to support parts of our recruitment process such as application screening, interview scheduling, and candidate communications. These tools are used to improve efficiency and consistency, but they do not replace human judgement. All hiring decisions are made by people, and we are committed to fair and unbiased assessment of every candidate. 

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