Full Stack Developer – Trading Platform Team Full Time NEW

Trading Platform Engineer

This is one of the largest multi-manager platforms in the world – a firm that allocates capital across dozens of independent investment teams spanning equities, fixed income, macro, and quantitative strategies globally. The technology function here is not a utility. It is a competitive advantage, and the trading platform is its most critical expression.

The systems you build will process order flow, market data, and risk calculations across asset classes and time zones simultaneously. Speed matters here – not at the co-location, kernel-bypass level, but at the level where architectural decisions about serialization, memory layout, and message routing have measurable impact on execution quality and operational resilience. Engineers who find that distinction interesting will thrive here.

The firm runs dozens of pods with real autonomy. Your platform serves all of them. Reliability is not a backlog item – it is the job.

What you will build

Core trading platform

• Design and develop high-throughput components of the order management, execution, and position keeping systems used across the firm’s global trading operations
• Build and optimize real-time market data distribution and order routing infrastructure — architected for deterministic, low-jitter performance under sustained load
• Own the systems that aggregate positions, P&L, and risk exposures across asset classes in real time, feeding both live traders and automated strategies
• Develop pre-trade and post-trade workflows that operate at the speed of the market day without degradation across peak volumes

Messaging and event infrastructure

• Architect and maintain Kafka-based event streaming pipelines that carry order events, market data, and risk signals between platform components with minimal latency overhead
• Design message schemas and topic architectures that are durable, evolvable, and operationally observable
• Ensure streaming infrastructure degrades gracefully under failure and recovers deterministically – trading does not pause for infrastructure incidents

Platform reliability and deployment

• Containerize and orchestrate trading platform services using Kubernetes, maintaining high-availability configurations appropriate for production trading environments
• Build and maintain CI/CD pipelines, deployment tooling, and rollback capabilities that allow rapid iteration without operational risk
• Instrument systems for observability: latency profiling, throughput metrics, alerting, and runbook-level operability

Research and quant tooling

• Build Python-based APIs, data interfaces, and tooling that give quant researchers and portfolio managers clean access to platform data and execution analytics
• Work with investment teams to translate performance and workflow requirements into platform capabilities — you are the interface between the trading floor and the technology stack

Technical environment

Core language C# / C++

Messaging Apache Kafka

Orchestration Kubernetes

Scripting / APIs Python

Protocols FIX / REST / gRPC

Environment Linux

Domains OMS / EMS / Risk

Observability Metrics / Tracing

Who you are

• 7+ years of software engineering experience with meaningful time spent in financial markets technology — OMS, EMS, risk systems, or market data infrastructure
• Deep C# or C++ fluency; you understand memory management, concurrency primitives, and what the runtime is doing under load
• Hands-on Kafka experience at production scale — topic design, consumer group management, exactly-once semantics, and operational ownership
• Production Kubernetes experience including deployment strategy, resource management, and failure recovery
• Genuine performance engineering instinct — you profile before optimizing and you understand why latency distributions matter more than averages
• Familiarity with FIX protocol and standard sell-side connectivity patterns
• Python sufficient to build usable tooling and APIs for research and trading consumers
• A preference for systems that are simple, observable, and fast over systems that are clever