Senior Java/Kotlin Engineer

Job Description

Job Description

We are looking for a Senior Java/Kotlin Engineer to work with our client - Tier 1 investment bank on its Equity Accelerator program, a multi-year strategic initiative to modernize the Prime Finance Equities platform. The program is re-engineering core trading systems, building new data and market-expansion platforms, and launching advanced client features such as cross-margining and credit financing, replacing legacy architecture with event-driven, cloud-native systems designed for institutional-grade stability, throughput and extensibility.
This is not a greenfield build. You will work directly within a complex, financially significant production system, critically assessing system behavior and data integrity in dynamic market environments, contributing to architectural decisions, and operating with a high degree of autonomy within an experienced engineering group. This is not general-purpose Java delivery: the domain complexity and the engineering standards applied by the internal team demand engineers with real depth.
Essential functions

• Re-engineering core trading and post-trade systems into event-driven, cloud-native services on the JVM (Java and Kotlin).
• Modernising legacy components while keeping a live, financially significant platform stable.
• Building the new data and market-expansion platforms that underpin the programme, and the plumbing for advanced client features such as cross-margining and credit financing.
• Designing for the realities of event-driven systems: failure handling, ordering guarantees, replay semantics, and data integrity under market pressure.
• Practising TDD and shift-left testing as the default. Local-first testing with containerised dependencies, fast feedback loops, and owning the quality of your deliverables end-to-end rather than handing it to a QA group.
• Delivering iteratively: trunk-based development, CI/CD, and frequent (weekly or better) production releases during business hours with no service interruption.
• Engaging directly with business stakeholders and upstream/downstream teams to build your own domain knowledge, rather than relying on Business Analysts to hold it for you.
• Using AI-assisted and agentic development tooling as a genuine accelerator for analysis of legacy code, test generation, prototyping and refactoring.

Qualifications

• Expert-level Java, with Kotlin experience or a clear appetite for it (enterprise-grade systems, multi-threading, performance).
• Practical experience designing and building event-driven systems on message-passing and event-sourcing patterns, including failure handling, ordering guarantees and replay semantics.
• Test-Driven Development as a practice, not an aspiration: you own quality end-to-end, you design for testability, and you can demonstrate it through how you approach a problem (this is assessed at interview).
• Hands-on experience in or alongside a capital markets trading or post-trade environment: the trade lifecycle, trade booking and position management, and post-trade operations such as cashflow calculation, settlement and wires, client reporting, and accounting principles. You should be able to back this up with concrete examples, not high-level familiarity.
• A track record in genuine iterative delivery incl. short feedback loops, trunk-based development, CI/CD, and regular zero-downtime production releases. No waterfall projects labelled as agile.
• Proven ability to analyse, refactor and modernise large-scale legacy systems while maintaining stability.
• Senior-level autonomy: you contribute to design discussions, push back constructively on technical decisions, and operate with minimal supervision in a complex production environment.
• Bachelor’s Degree in Compute Science or similar major.

Would be a plus

• Understanding of Prime Brokerage, Synthetic (Swap) or Cash Equity operational flows. This is a significant advantage.
• Familiarity with corporate actions, regulatory reporting obligations (e.g. 871(m), EMIR, MiFID), and integrating with risk/valuation systems in an equities context.
• Strong SQL Server depth: T-SQL, schema design, performance tuning and complex data models in high-transaction environments.
• Kafka (or comparable event-streaming platforms) at scale, and MongoDB.
• Kubernetes/OpenShift deployment and cloud-native operational practices, with observability via OpenTelemetry, ELK and Grafana.
• Demonstrated AI-first development experience: agentic coding workflows for legacy analysis, refactoring and test generation, with a clear-eyed view of where the tools help and where they don’t.