Site Reliability Engineer - Algorithmic Trading
Posted Aug 19, 2026 · We last checked this listing on Oct 6, 2026
Likely interview questions for this role
Written from this job description, not a generic list. Each one notes what the interviewer is really checking.
About your past
Tell me about a time you wrote software, not just scripts, to make a system more reliable.
What they are checking: Whether they work at the intersection of software and infrastructure that the role describes.
Tell me about a production incident you caused. What happened and what changed afterward?
What they are checking: Honesty and whether they turned their own mistake into safer deploys or checks.
How do you work with quant researchers who want to move fast while you want stability?
What they are checking: Whether they can make safe paths easy instead of acting as a gate that slows research.
What would you do
The team keeps production trading, the test environment and the research pipeline running. How would you prioritize when all three have problems at once?
What they are checking: Whether they protect live trading first and communicate clearly with researchers whose work is delayed.
A strategy suddenly starts sending far more orders than usual. What do you do in the first two minutes?
What they are checking: Whether they know when to escalate to traders or pull a kill switch rather than quietly debugging while risk builds.
About the work
We want someone who builds observability that surfaces issues before they become problems. What would you monitor on an algorithmic trading system that a generic setup would miss?
What they are checking: Whether they understand trading signals like fill rates, order rejects, latency and position drift, not just CPU and memory.
How would you troubleshoot a rise in latency between our trading system and an exchange?
What they are checking: A layered approach across application, host, network and exchange side, using timestamps to locate the delay.
How do you make a test environment match production closely enough that it catches real problems?
What they are checking: Understanding of market data replay, config parity and the gaps that make tests pass but production fail.
Walk me through how you would reduce alert noise for a team that has started ignoring alerts.
What they are checking: Whether they tie alerts to real impact and tune or delete them so pages mean something again.
How would you design a deployment process for trading code that may need to roll back mid-session?
What they are checking: Thinking about safe rollout windows, fast rollback and state like open orders during a change.
What Linux tools do you reach for when a trading process is slow but the logs look normal?
What they are checking: Comfort with perf, strace, tcpdump and system metrics to find problems logs do not show.
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Practice this out loudThe full job description
As published by DRW.