What we do?
We're building the firm's next-generation regulatory reporting platform - and we're building it with agentic AI tooling in the loop from day one.
Controllers Engineering
Controllers Engineering designs and builds the systems behind the firm's financial measurement and reporting — revenue, balance sheet, liquidity and capital. We meet the firm's global regulatory financial reporting obligations and build the tooling that makes controller functions faster and more consistent.
Controllers Engineering — Reporting
Our engineers are using agentic AI coding tools as part of day-to-day development. We pair them with spec-driven development: we write the specification, the agent writes the first draft, and the engineer owns the outcome.
We're using that toolchain to build a single reporting platform on AWS that ingests firmwide financial data, applies common data models and reusable validation and exception workflows, and produces submissions for regulators worldwide — replacing dozens of fragmented legacy processes.
No prior finance or regulatory reporting experience needed. We'll teach you the domain.
What you'll do
Build and own the systems that produce the firm's regulatory submissions to global regulators
Take features end to end in an Agile team — requirements, design, code, test, UAT, release and run
Produce technical designs, testing strategies and implementation plans
Work directly with Finance stakeholders to turn regulatory requirements into workflows, data requirements and specifications
Build reusable solutions other teams can adopt, and spot opportunities to collaborate across divisions
Contribute to data modelling and curation for large-scale financial datasets
What you'll need
Bachelor's degree or equivalent practical experience in a numerate/technical discipline
4+ years of software development experience
Strong analysis and design skills, including data structures, algorithms and performance-oriented design
Hands-on programming experience in Java
Strong communication skills with both technical and business audiences
We'd also love to see (you don't need all of these)
Working knowledge of cloud, ideally AWS (S3, SQS, Lambda, Fargate) or equivalents
Experience with distributed, microservices-based applications
Solutions architecture and system design experience
Strong database and data modelling skills
Experience with agentic AI coding tools (Claude Code, Copilot Agent Mode, Devin) and spec-driven development
Big data / Lakehouse (Snowflake), ETL pipelines (Spark, Glue), or event streaming (Kafka)
Interest in investment banking or financial instruments