Engineering Manager: Trading Systems Leader

Kraken

Dubai

Hybrid

AED 661,000 - 955,000

Full time

2 days ago
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Job summary

Kraken is seeking an Engineering Leader to lead and grow a team of 8–10 engineers working on core trading backend services, including the matching engine and data gateways. You will guide the stack evolution from legacy to modern implementations while remaining hands-on when needed.

You will stay technically close to the architecture to unblock issues, push performance and market data work, and promote AI-assisted practices.

Qualifications

  • Experience leading teams of 8–10 engineers.
  • Hands-on with Linux-based distributed systems and low-latency environments.
  • Proficient in Rust and/or C++ and familiar with Go and Python.
  • Knowledge of order types, trading systems, and financial products.
  • Experience with Aeron or similar messaging systems.
  • Comfort with multicast-based market data distribution.
  • Crypto familiarity is highly preferable.
  • Demonstrated ability to prioritize under aggressive deadlines.

Responsibilities

  • Lead and grow a team of 8–10 engineers owning core trading backend services.
  • Guide evolution from legacy systems to modern replacements in the stack.
  • Stay technically close to the stack to unblock and contribute to architecture decisions.
  • Champion performance and market data work as top priorities.
  • Introduce AI-assisted engineering practices within the team.
  • Partner with product and other engineering pods to drive roadmap execution.
  • Represent the team technically with peers and stakeholders.

Skills

Mgmt experience
Rust
C++
Go
Python
Low-latency
Distributed systems
Trading knowledge
Leadership

Education

BS in technical field

Tools

Aeron
Linux

Job description

Kraken is seeking an Engineering Leader to lead and grow a team of 8–10 engineers working on core trading backend services, including the matching engine and data gateways. You will guide the stack evolution from legacy to modern implementations while remaining hands-on when needed.

You will stay technically close to the architecture to unblock issues, push performance and market data work, and promote AI-assisted practices.

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