Principal Engineer

Full time role for experienced engineers

We are partnering with a technology company founded by industry veterans with deep expertise in enterprise architecture and quantitative systems. We are building their core engineering team to turn complex business and quantitative ideas into working software. The work spans understanding unfamiliar domains, designing systems, investigating difficult problems, and delivering reliable solutions.

We value engineers who ask precise questions, reason from fundamentals, explore beyond familiar tools, and develop their own informed view. We actively use AI in research and development. You should be able to direct these tools, understand the resulting work, and verify that it solves the problem.

The opportunity

You will work directly with decision makers and domain experts in a small team with a flat structure. The work spans problem definition, system design, implementation, investigation and production operation.

Data processing is one part of the work. The role calls for the ability to move between unfamiliar problems, understand the principles that govern them and develop an informed view of what to build.

What you will do

• Turn incomplete requirements into a clear problem statement. Understand who needs the solution, which constraints matter and how success will be measured.
• Investigate difficult questions through reading, calculations, profiling and experiments. Separate observations from assumptions and find the causes that affect the decision.
• Compare plausible approaches, explain their costs and limitations, and make a recommendation. Challenge the proposed direction when the evidence supports a better one.
• Build and operate solutions across their lifecycle, including testing, deployment, security, data correctness and recovery from failure.
• Create code, interfaces and tools that other engineers can understand and extend. Use engineering review to improve decisions and share what you learn.

How responsibility works

You will have substantial autonomy and direct accountability for your decisions. We expect you to recognise when a decision needs more evidence or input from others, make uncertainty visible and adjust the plan when new information changes it.

What we are looking for

• Strong programming ability and a practical understanding of algorithms, data structures, state, concurrency and system behaviour. You can explain the mechanisms behind a design and recognise the limits of your knowledge.
• Experience delivering substantial software and taking responsibility for its behaviour in use. You can discuss a concrete decision, its alternatives and what happened after delivery.
• Breadth developed through different problems, systems or domains. You can transfer useful ideas between them and explain where an analogy stops being valid.
• A habit of investigating fundamentals. You have examples of pursuing a question beyond the first answer because understanding it changed the solution.
• Clear communication with engineers and people outside engineering. You can make a recommendation understandable without hiding its uncertainty or tradeoffs.

Evidence of these abilities matters more than a particular job title or number of years. Experience in quantitative work, financial markets, demanding performance problems or complex data systems can be useful. Specific frameworks, market terminology and a history of processing millions of events per second are optional strengths.

Working with AI

We actively use AI in research and software development. You should be able to direct these tools, investigate unfamiliar technologies and inspect the resulting code or reasoning. Responsibility for understanding the solution, checking important assumptions and verifying the outcome stays with the engineer.

What to share with us

Bring examples of work you helped deliver, a difficult problem you investigated and a decision you changed after learning something new. Explain your own contribution and the evidence behind your conclusions. Respect any confidentiality restrictions on previous work.

Our technical discussion uses a fictional case and a small practical exercise. AI and reference materials are allowed. We assess your reasoning, investigation and ability to verify a result. Familiarity with a particular streaming framework is not required.

Location and work pattern

Full time. Flexible hybrid working, with on-site presence as needed.

Key hubs are London, Cambridge, New York.