Stanford Black Limited
Production Support Engineer

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Production Engineer – Equities | AI & Automation | London
A leading global multi-strategy hedge fund is seeking a Production Engineer to join its Equities technology function, helping transform how front-office technology is supported through automation, AI, and modern production engineering practices.
This is a 70/30 engineering-to-support role. The majority of your time will be spent building automation, tooling, monitoring, and AI-driven solutions that improve how the team operates, with the remainder focused on supporting Portfolio Managers and ensuring critical equity trading systems are running effectively. The team is currently undergoing a significant transformation, moving away from traditional production support towards an engineering-led model built around automation, observability, and AI. You'll have the opportunity to play an active role in that change, identifying areas of manual effort and developing solutions that fundamentally improve how the team supports the business. The environment is particularly well suited to engineers who are curious about AI and want the opportunity to apply it to real production problems.
The Role
- Spend the majority of your time designing and building automation and tooling to improve the efficiency, reliability, and scalability of front-office support
- Identify repetitive or inefficient processes and develop long-term engineering solutions rather than relying on manual intervention
- Develop Python-based automation and applications, with scope to explore AI agents, conversational interfaces, and other emerging technologies
- Build and improve monitoring and observability across critical trading systems, using platforms such as Geneos, Zabbix, Grafana, and similar tooling
- Work directly with Portfolio Managers and investment teams to understand workflows and identify opportunities for automation or improvement
- Ensure equity trading platforms are operational each morning and investigate production issues impacting the trading desk
- Support Portfolio Managers with production issues, trade discrepancies, breaks, order allocation, and routing
- Liaise with brokers and other external parties to investigate issues and resolve trade-related problems
- Develop a detailed understanding of the equity trade lifecycle, including the practical implications of contracts, execution, routing, and booking
- Troubleshoot issues across Windows and Linux environments, working across application, infrastructure, and connectivity layers where required
- Contribute to the continued evolution of the team's production engineering model, helping define new processes, tooling, and ways of working
Reasons to use Rodeo
I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?
Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.
Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.
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Graduate Consultant — 2026 Scheme
Why you're a good match
StrongYour economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.
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Why you're a good match
You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.
Experience fit
Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.
Only hits
No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
Requirements
- Experience within Equities production support, production engineering, application support, or a similar front-office technology environment
- Strong understanding of Equities trading and the full trade lifecycle
- Strong Python experience, ideally with evidence of using it to automate processes or build internal tools
- An engineering-first mindset, with a natural focus on how problems can be solved permanently rather than repeatedly worked around
- Strong monitoring and observability experience, ideally with Geneos, Zabbix, Grafana, or similar platforms
- Experience working closely with Portfolio Managers, Traders, or other front-office stakeholders
- Strong troubleshooting and analytical skills across complex production environments
- Exposure to FIX is highly desirable
- Experience working across both Windows and Linux environments would be advantageous
- Genuine interest in AI and emerging technologies, with an appetite to identify practical ways they can improve production operations


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Company Highlights
- Technology-led investment firm where engineering is viewed as a core competitive advantage
- Significant investment across both discretionary and systematic trading platforms, creating a strong pipeline of technology transformation and greenfield engineering work
- Work directly alongside Portfolio Managers, Traders, Quantitative Developers, and Researchers, offering genuine business exposure and influence
- Strong investment in AI, automation, and engineering-led production support, with the opportunity to work on solutions that materially change how technology is delivered to the front office
- Highly collaborative culture with small, autonomous teams backed by the resources of a globally recognised investment firm
- Broad exposure across trading technology, creating opportunities to develop both technical and business expertise
- Strong long-term career progression with the opportunity to move deeper into production engineering, automation, platform engineering, or adjacent technology functions
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