UK

United Kingdom · Technology and data · Senior (5-8 years)

Senior Algorithmic Trading Engineer

Here is the whole job, in plain words. What it is, what you decide, how you're judged, how people get here and where they go next. Then the part no course gives you: twelve AI tutors who learn your work.

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  • Experience bandSenior (5-8 years)
  • Direct reportsNo direct reports
  • Reports toLead Algorithmic Trading Engineer (L4) or Algorithmic Trading Engineer Manager (L5)
  • UK framework levelUsually a manager, or the deepest specialist in a team

Also advertised as Senior Low-Latency Engineer · Senior Quant Developer · Senior Trading Systems Engineer · Senior HFT Engineer

Built on 43,079 real UK job descriptions we analysed · grounded in qualifications employers recognise

Two short quizzes about you

1From this job to a course

The qualifications matched to this job

No confident skill match yet for Senior Algorithmic Trading Engineer. The closest we hold is below.

ETCAL Level 3 NVQ Diploma in Engineering Technical Support ETC Awards Limited · Level 3 · covers 1 of 1 standard

Matched from the standards this job is measured against: a suggestion, not an official ruling.

The units you would start with

Performing Low Level Programming for Engineering Software ETCAL Level 3 NVQ Diploma in Engineering Technical Support
Developing low level engineering software EAL Level 4 Diploma in Engineering and Advanced Manufacturing (Development Competence)

The future skills this job leans on

AI Fluency working with AI as a thinking partner
Data Fluency turning numbers into a decision
Automation Fluency building AI into how work runs
Systems Fluency seeing the whole picture
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Your Plan Illustration

Built for Senior Algorithmic Trading Engineer

2 units that map to this job, from the qualifications that cover it.

  1. Performing Low Level Programming for Engineering Software ETC Awards Limited · covers 1 of 1 standards Level 3
  2. Developing low level engineering software Excellence, Achievement & Learning Limited · covers 1 of 1 standards Level 4
These are the real units behind this job, in the order they rank for it. Nothing here is marked done, because this plan has not been started by anyone yet. Yours would fill in as you go.

2AI and this work

Will AI change your work as a Senior Algorithmic Trading Engineer?

Nobody can say exactly how. Here is what this job is being asked for next, and where to start.

The new skill this role is being asked for

  • Prompt Engineering & LLM Integration for Code/Analysis
Why each one is rising

The future skills this job leans on

We'll only ever tell you what we can actually back up. No hype, no scare tactics.

What happens when you start

Next, a free account. We build your Senior Algorithmic Trading Engineer plan as you set up, starting with a Future Fluency module on using AI in your job. No card.

Your first Future Fluency module is free. After that, your AI tutor is £70 a month.

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3What this role really is

This job involves designing, building and optimising the high-performance systems that execute trades at speed. It means engineering for milliseconds, sometimes nanoseconds, where every line of code matters. It involves handling complex technical challenges, making sure systems stay fast, reliable and able to handle millions of transactions daily.

4What you'd actually use

The tools this job runs on, and how well you'd need to know each one.

C++ (17/20/23) Advanced

Designing and optimising performance-critical, multi-threaded trading engines, market data handlers, and order management systems. You'll be using STL, Boost, and modern C++ features for low-latency code.

Python (3.x) (pandas, NumPy, SciPy, Cython) Advanced

Building and maintaining complex research and backtesting frameworks, automating deployment and monitoring scripts, and profiling/optimising Python code for performance (e.g., with Cython).

Kdb+/q Advanced

Designing efficient Kdb+ schemas, writing complex q functions for high-throughput data aggregation and signal generation, and managing tick data capture for historical and real-time analysis.

FIX Protocol Advanced

Implementing and certifying FIX engines from scratch, managing complex order routing logic, and deeply understanding session-level state management for exchange connectivity.

Linux/Bash (kernel tuning, `perf`, `gdb`) Advanced

Optimising the OS for low latency (kernel tuning, CPU pinning, interrupt handling), writing complex Bash scripts for deployment and monitoring, and using advanced debugging/profiling tools.

AWS (EC2, S3, Lambda, Terraform) Intermediate

Designing and deploying scalable backtesting clusters using EC2 Spot Fleets, Lambda, and Step Functions. Managing infrastructure as code with Terraform for cloud-based research environments.

Jenkins/Git (CI/CD) Advanced

Designing and building complex CI/CD pipelines for C++ and Python applications, including automated testing, static analysis, performance benchmarks, and zero-downtime deployments. You'll be setting the standards here.

5What you get to decide, and how that grows

Power in a job isn't your title. It's what you're allowed to decide. Here's how it grows as you move up.

The choiceComing in Where you are nowThe step above
Technical Design & Implementation Follows established design patterns; implements features from detailed specs; all code reviewed by senior engineer. Chooses appropriate design patterns for routine problems; implements features independently; seeks review for complex parts. Leads technical design for new, complex components; defines design patterns for specific workstreams; makes key technology choices within scope; consults on major architectural shifts.
Production Incident Response Assists with data gathering and log analysis under direct supervision; escalates immediately. Diagnoses and resolves routine P3/P4 incidents independently; escalates P1/P2 incidents with initial analysis. Leads diagnosis and resolution for P1/P2 incidents on owned components; coordinates with other teams; drives post-mortem analysis and preventative measures.
Code & System Optimisation Identifies obvious performance bottlenecks; implements suggested optimisations. Profiles and optimises specific code paths; proposes and implements minor system-level tuning. Deeply profiles and optimises critical low-latency paths (C++, kernel, network); researches and implements advanced optimisation techniques (e.g., lock-free, kernel bypass); sets performance benchmarks.
Mentorship & Knowledge Sharing Asks questions and learns from senior team members; documents own learning. Provides informal guidance to new joiners; contributes to team documentation. Actively mentors 0-2 junior engineers (code reviews, unblocking, technical guidance); leads internal tech talks; contributes significantly to internal knowledge base and best practices.
Budget & Resource Allocation No authority; requests resources via supervisor. Requests specific tools or resources for projects; provides estimates for tasks. Recommends specific hardware/software purchases up to £5K for owned components; provides detailed resource estimates for workstreams; influences project prioritisation based on technical feasibility and cost.

6How you'll be judged

The scoreboard, and what is not on it. The hard targets, how often each is actually looked at, and the quiet signals that never reach a dashboard.

Tick-to-Trade Latency Reduction
The time it takes from receiving a market data tick to sending an order in response.
Target · Reduce median latency by >1 microsecond per quarter on owned components

Delivered a new market data handler that shaved 1.5 microseconds off the average tick-to-trade latency for a major exchange in Q2.

System Uptime & Stability
The availability and error-free operation of the trading components you own during market hours.
Target · Maintain 99.999% uptime for critical components; <1 P1/P2 incident per quarter

Your execution engine ran for an entire quarter without a single P1 or P2 incident, even during periods of high market volatility.

Project Delivery & Timeliness
Successfully leading and completing significant technical projects or workstreams within agreed timelines and scope.
Target · Deliver 90% of assigned projects on time and within scope

Successfully led the implementation of a new FIX gateway for a major broker, delivering it two weeks ahead of schedule and passing all certification tests on the first attempt.

Backtest Framework Performance
The speed and accuracy of the backtesting infrastructure you've designed or optimised.
Target · Improve backtest run times by 10-15% annually or support 20% more simultaneous research jobs

Re-architected the historical data ingestion pipeline, allowing quants to run backtests 1.5x faster, leading to quicker alpha discovery.

Technical Leadership & Mentorship
Providing clear technical guidance, setting best practices, and effectively mentoring junior engineers.
  • You're the first person junior engineers come to for complex coding problems. Your code reviews are insightful and constructive. You regularly contribute to our internal technical wiki and lead knowledge-sharing sessions. Mentees show demonstrable growth and take on more complex tasks.
Problem-Solving & Incident Response
Your ability to calmly and effectively diagnose and resolve complex production issues, especially during critical outages.
  • During a system outage, you're the one systematically isolating the root cause, communicating clearly, and implementing a fix under pressure. Post-incident reviews highlight your key role in resolution and your proactive suggestions for future prevention. You're the person who can debug a race condition that only appears once a month.
Collaboration with Quants & Traders
Translating complex trading requirements into technical specifications and explaining technical constraints clearly to non-technical stakeholders.
  • Quants consistently praise your understanding of their research needs and your ability to build systems that support their ideas. Traders trust your judgement on system capabilities and limitations. You can explain why a 'simple' feature might take weeks to build without sounding dismissive.
Proactive System Improvement
Identifying and addressing technical debt, performance bottlenecks, and potential risks before they become critical problems.
  • You regularly propose and implement optimisations that aren't 'urgent' but improve system health long-term. You've identified a potential memory leak or a network configuration issue that could cause problems down the line and taken steps to mitigate it. You're always looking for ways to shave off those nanoseconds.

7Would you like it

Both sides. What people enjoy, and what grinds them down.

What people enjoy
Direct Impact on P&L

You'll see your code's performance directly reflected in trading results, knowing that every nanosecond saved or bug fixed contributes to the firm's profitability. This isn't abstract; it's tangible financial impact.

Optimising a market data parser that reduces latency by 200ns, which directly leads to an increase in successful arbitrage opportunities for a specific strategy, adding £X to the daily P&L.

Solving Extremely Hard Technical Problems

You'll be tackling challenges at the absolute limits of computer science and network engineering—think multi-threaded concurrency, kernel bypass, and optimising for CPU cache lines. If you love deep technical puzzles, you'll be in your element.

Diagnosing and fixing a rare race condition in a multi-threaded execution engine that only manifests under specific, high-load market conditions, requiring deep understanding of memory models and synchronisation primitives.

Continuous Learning & Innovation

The technology landscape in algorithmic trading moves incredibly fast. You'll be constantly learning new languages, hardware architectures, and optimisation techniques to stay ahead. If you're not learning, you're falling behind, and that's a motivator here.

Researching and implementing a new low-latency network protocol or exploring FPGA programming to offload critical trading logic, staying ahead of industry trends.

What frustrates people
  • The 'simple' request from a quant that requires a fundamental, multi-week rewrite of a core component.
  • Spending days trying to replicate a bug that only occurs during specific, rare market conditions.
  • Optimising code by 100 nanoseconds, only to have network jitter or an exchange's system introduce a 5-microsecond spike.
  • Discovering that 'clean' historical data has corrupt timestamps, invalidating months of backtesting.
  • The constant tension between refactoring technical debt and the business pressure to deliver new alpha strategies.
  • Explaining why a £250K hardware purchase is essential for a sub-microsecond latency gain to someone who can't perceive it.
What this role does not give you
  • A slow, predictable pace where you can ease into tasks.
  • A role where you only work on greenfield projects with no legacy systems to maintain.
  • A environment where technical decisions are made without considering their direct financial impact.
  • A job where you don't have to deal with high-pressure situations or production outages.

8Who you work with

This role directly impacts our trading profitability and our ability to compete in high-frequency markets. Your work ensures our strategies can react to market events faster and more reliably than our rivals. A well-engineered system here means more successful trades, fewer errors, and a stronger competitive position. Conversely, any technical flaw or delay can lead to immediate financial losses and reputational damage. You're essentially building the bedrock for our quantitative edge.

Inside the business
  • Quantitative Researchers (Quants)
  • Traders and Portfolio Managers
  • Risk Management Team
  • Infrastructure and Operations Teams
  • Other Senior Engineers and Leads
Outside the business
  • Exchange Technical Support
  • Market Data Vendors
  • Brokerage Technical Teams
  • Hardware Vendors (e.g., network cards, FPGAs)

9What you need before you start

Not a wish list. The things you would be expected to already have.

  • Proven ability to independently own and deliver complex software components in a high-performance environment (e.g., a market data handler, an order routing module).
  • Demonstrable experience with advanced C++ programming, including multi-threading, network programming, and performance optimisation.
  • Solid understanding of data structures and algorithms, and how to apply them efficiently in a low-latency context.
  • Experience debugging complex production systems under pressure, using tools like `gdb` or `perf`.
  • A track record of effective collaboration with quantitative researchers or traders to translate requirements into technical solutions.
  • Experience with version control systems (Git) and CI/CD pipelines.

10What to practise next

Where the job is going, and what to do about it starting this week.

FPGA Programming & Hardware Acceleration

As software-based latency reductions hit physical limits, the next frontier is offloading critical trading logic (e.g., market data parsing, simple strategy execution) directly onto Field-Programmable Gate Arrays (FPGAs). This offers sub-microsecond latency advantages that are increasingly crucial.

Hardware Description Languages (VHDL/Verilog) · High-Level Synthesis (HLS) · Network Interface Card (NIC) Offload · Tick-to-Trade in Hardware

  • This quarter: Take an online course on VHDL/Verilog or High-Level Synthesis.
  • Next quarter: Get familiar with our existing FPGA infrastructure (if any) and shadow a team member working on hardware projects.
  • Month 6: Contribute to a small proof-of-concept project involving FPGA offload for a non-critical task.
  • Month 9: Propose a specific trading component that could benefit from FPGA acceleration, outlining the technical and commercial case.

Quick win: Start reading whitepapers from companies like Xilinx or Intel on FPGA applications in finance. Understand the fundamental latency benefits and limitations.

Advanced Network Stack Optimisation & Kernel Bypass

The network is often the biggest bottleneck for tick-to-trade latency. Deep expertise in optimising the entire network stack, from the NIC driver to the application layer, including kernel bypass techniques, will become non-negotiable for competitive trading.

DPDK (Data Plane Development Kit) · Solarflare/Mellanox OpenOnload · TCP/UDP Protocol Tuning · PTP (Precision Time Protocol)

  • This quarter: Deep dive into the Linux networking stack. Read 'TCP/IP Illustrated' if you haven't already.
  • Next quarter: Experiment with DPDK in a test environment. Build a simple packet forwarder.
  • Month 6: Take ownership of our network configuration and monitoring tools for a specific trading segment.
  • Month 9: Propose and implement a network optimisation project that demonstrably reduces latency for a critical path.

Quick win: Familiarise yourself with `ethtool`, `ip route`, and `sysctl` settings on our production machines. Understand what each parameter does and its impact on latency.

11Staying current once you are in

What people here do to keep up
  • Regularly contribute to open-source projects, especially those related to low-latency networking, high-performance computing, or financial data processing.
  • Attend industry conferences (e.g., CppCon, SIGCOMM, QuantMinds) to stay abreast of the latest technical advancements and market trends.
  • Actively participate in online technical communities (e.g., Stack Overflow, specific C++ or HFT forums) to share knowledge and learn from peers.
  • Pursue advanced online courses or certifications in areas like parallel computing, distributed systems, or specific hardware acceleration techniques (e.g., CUDA, FPGA programming).
  • Lead internal technical workshops or 'lunch and learn' sessions to share your expertise with the wider engineering team.

12The rising capability

The rising capability

Zavmo analysis

What's rising in its place

This is where the work is heading, and the higher pay with it. Get fluent here and the shift stops being a threat and starts being your edge.

Prompt Engineering & LLM Integration for Code/Analysis

Competitors are already using Large Language Models (LLMs) to draft complex C++ code, analyse backtest results, and summarise dense exchange specifications in minutes, tasks that used to take hours or days. Engineers who master this will significantly outproduce their peers and unlock new levels of efficiency. This isn't future-gazing; it's happening now.

  • Context Windows & Token Limits
  • Temperature Settings & Determinism
  • Retrieval Augmented Generation (RAG)
  • Output Validation & Hallucination Detection
  • Prompt Chaining & Agentic Workflows

13What you’ll use

What you’ll use

Skills this role draws on

Technical

  • Market Microstructure Analysis
  • Low-Latency Programming Techniques
  • Backtesting & Simulation Frameworks
  • Systematic Risk Management Implementation
  • Multi-threaded & Concurrent Programming

14The pathway

The pathway

How you actually get there, here

How you become one varies far more by country than what one does. This is the UK route. Most people take one of these ways in; the right one depends on where you're starting from.

  1. 1

    Promotion from Algorithmic Trading Engineer (L2)

    2-4 years as an L2

    Skills to master

    • Taking full ownership of complex components, leading technical designs, demonstrating strong problem-solving in production, and starting to mentor junior colleagues.

    You're ready to move on when

    • Consistently delivering complex features independently, with minimal supervision.
    • Proactively identifying and fixing system bottlenecks or technical debt.
    • Being the 'go-to' person for a specific system component or technology.
    • Successfully guiding new team members or less experienced engineers on technical tasks.
    • Demonstrating a deep understanding of market microstructure and its impact on system design.
  2. 2

    Direct Entry from another HFT/Prop Trading Firm

    5-8 years of relevant experience

    Skills to master

    • Proven track record of designing and implementing low-latency trading systems, deep expertise in C++ and relevant technologies, and experience with demanding production environments.

    You're ready to move on when

    • Experience with a similar tech stack and market domain.
    • Ability to quickly integrate into a new codebase and contribute effectively.
    • Demonstrated ability to lead technical discussions and influence architectural decisions.
    • Strong references from previous roles highlighting technical leadership and impact.
  3. 3

    Transition from High-Performance Computing (HPC) or Scientific Computing

    6-10 years of experience, with a focus on self-directed learning in finance

    Skills to master

    • Adapting HPC optimisation techniques to financial market data, rapid learning of financial instruments and market microstructure, and understanding the regulatory landscape.

    You're ready to move on when

    • Demonstrable experience optimising code for extreme performance (e.g., scientific simulations, game engines).
    • Strong C++ skills, especially in multi-threading and memory management.
    • A genuine passion for financial markets and a proactive approach to learning the domain specifics.
    • Ability to work in a high-pressure, real-time environment.

15Where this role leads

The long view: This work can lead to managing engineering teams as a Director of Trading Technology. It can also lead to setting technology strategy as a Chief Technology Officer. Some move into quantitative finance as Head of Quantitative Research.

The ten Future Fluencies

Zavmo analysis

The credential is what you can do today. These are what keep you valuable.

A qualification proves you can do the job as it's defined today. These ten are what decide whether you're still the obvious person for it in five years. They're the capabilities employers are now writing into senior roles faster than people are learning them. Zavmo weaves them through whatever you study, so you come out with both: the credential and the fluency.

The highlighted ones are the Fluencies your role leans on hardest, from how Senior Algorithmic Trading Engineer is actually changing.

Where it leads

Roles this leads to

How you would learn this

One to one, on the work you already do

A tutor sets the task against your own job and marks the reasoning, at your pace. There is no cohort to fall behind.

A lesson from Performing Low Level Programming for Engineering Software, worked against Senior Algorithmic Trading Engineer.

Performing Low Level Programming for Engineering Software Level 3

Applied to your work in Senior Algorithmic Trading Engineer

This unit aims to equip learners with the ability to perform low level programming for engineering software applications, including developing, testing, and debugging code. Learners will demonstrate the ability to write efficient and optimised code and integrate it with higher-level components. Furthermore, they will understand the principles of low level programming languages and their applications in engineering.

How the thinking builds
  1. 1 Remember
  2. 2 Understand
  3. 3 Apply
  4. 4 Analyse
  5. 5 Evaluate
  6. 6 Create
An illustration of a Zavmo lesson, built from this role’s own route. The unit, its objective and every criterion above are the awarding body’s own words, not an example.

It is £70 a month, billed monthly. Your free first module is Future Fluency, and you can cancel any time.

Start my Senior Algorithmic Trading Engineer plan, free
See Your Progress Grow Illustration
Senior Algorithmic Trading Engineer
  • Market Microstructure Analysis
  • Low-Latency Programming Techniques
  • Backtesting & Simulation Frameworks
  • Systematic Risk Management Implementation
  • Multi-threaded & Concurrent Programming
This is your Mind Palace on learn.zavmo.ai. Every skill above comes from this role's own record, not an example borrowed from another job. A node lights up when you evidence it, and what you build stays yours between jobs. That is the part a course cannot do.

16The detail, folded away

Everything else the record holds

The career branches in full, how AI is already showing up in the day-to-day, and the questions people ask about this job. Here when you want them, out of the way while you decide.

Where it leads next, rung by rung

Where it leads

The career path, and where it branches

Senior Algorithmic Trading Engineer is a start, not a ceiling. Each step below asks for new skills and hands back more autonomy.

  1. Lead Algorithmic Trading Engineer (L4)

    3-5 years as a Senior Engineer

    This is a significant step up, moving from owning workstreams to architecting solutions across multiple systems and setting technical direction for a small team. You'll also likely start managing direct reports.

    • Advanced Distributed Systems Design Architecting resilient, scalable, and fault-tolerant trading systems.
    • Vendor Management Evaluating and selecting external technology vendors.
    • Mentoring at Scale Guiding multiple engineers and fostering a high-performing team culture.
    • System-wide Performance Tuning Optimising performance across the entire trading stack, not just individual components.

  2. Principal Algorithmic Trading Engineer (L5 - Individual Contributor Path)

    5-8 years as a Senior Engineer

    This is the highest Individual Contributor (IC) level, focused on solving the firm's most challenging technical problems, setting technical standards, and driving innovation without direct people management responsibilities.

    • Advanced Research & Development Leading R&D efforts into entirely new technologies or optimisation techniques.
    • Cross-Organisational Influence Influencing technical decisions across different engineering teams and departments.
    • Mentoring Senior Engineers Guiding and advising other senior and lead engineers.
    • Technical Due Diligence Evaluating potential M&A targets or new technology investments from a deep technical perspective.
Working with AI on the job

Working with AI

Where AI is starting to help

Let's be real, even as a Senior Algorithmic Trading Engineer, you've got tasks that eat into your valuable time—the stuff that's important but not necessarily 'shaving nanoseconds' important. Imagine if you could offload some of that, freeing you up to focus on the truly hard, impactful engineering work. Well, you can.

AI isn't here to replace you; it's here to make you a more efficient, more effective engineer. We're talking about tools that can help you write better code faster, spot issues before they become problems, and even make sense of dense exchange specifications in minutes. This isn't science fiction; it's what our best engineers are already doing, and we want you to be part of it.

Smart Code Generation & Refactoring

Use AI assistants like GitHub Copilot or similar LLM-powered tools to generate boilerplate C++ for market data parsers, Python scripts for backtest analysis, or even complex unit tests. Feed legacy code snippets to an LLM to suggest modern C++ refactoring patterns, identify potential performance bottlenecks, or explain obscure template metaprogramming. It's like having a hyper-intelligent pair programmer available 24/7.

Anomaly Detection in Logs

Instead of manually sifting through terabytes of log files during a production outage (a truly dreadful task, honestly), use an AI tool to analyse real-time log streams. It can automatically flag anomalous behaviour—think sudden latency spikes, unusual message patterns, or unexpected error rates—and even suggest a probable root cause. This can cut incident resolution time dramatically, which is priceless when every second costs money.

Exchange Spec Summarisation

When a major exchange drops a new 300-page PDF detailing API changes, it's a nightmare to digest. Feed that monster to an LLM. It can quickly extract a concise summary of breaking changes, identify all impacted FIX message types, and even generate a preliminary checklist of required development tasks. This can save you days of tedious reading and ensure you don't miss a critical detail.

Automated Backtest Sanity Checks

After a backtest run, have an AI agent analyse the results for common pitfalls. It can automatically flag signs of overfitting, look for unrealistic fill rates, identify data inconsistencies, and even write a preliminary summary of the strategy's performance and potential weaknesses. This frees up quants and engineers to focus on deeper analysis, rather than basic validation.

Common questions

Common questions

How do you become a Senior Algorithmic Trading Engineer?

Common routes in include Promotion from Algorithmic Trading Engineer (2-4 years as an L2), Direct Entry from another HFT/Prop Trading Firm (5-8 years of relevant experience) and Transition from High-Performance Computing (HPC) or Scientific Computing (6-10 years of experience, with a focus on self-directed learning in finance). Times vary with prior experience.

Where can a Senior Algorithmic Trading Engineer progress to?

This role can lead on to Lead Algorithmic Trading Engineer (3-5 years as a Senior Engineer) and Principal Algorithmic Trading Engineer (5-8 years as a Senior Engineer), depending on the skills you build.

What new skills matter most for a Senior Algorithmic Trading Engineer?

Increasingly, Prompt Engineering & LLM Integration for Code/Analysis. These are the skills our record of this role lists as growing.

Free tools

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17Where to go from here

Other roles at Level 5

Same depth of qualification, different job. Useful if the work appeals but this particular role does not.

 More jobs in technology and data

Stay in the field you know and move sideways rather than up.
If you leave this industry

The skills built in this role, especially low-latency systems, distributed computing and performance optimisation, transfer to other high-performance sectors. These include scientific computing, advanced manufacturing and deep-tech startups. Engineers who can build fast, reliable systems are needed across many industries.

This role profile is © 2026 Growth Engineering Technologies Ltd. Built from UK occupational standards and regulated qualification data, and written for Zavmo.

You're not behind. You're right on time. The shift is only just beginning. Your role won't look the same in two years. Be the one who leads the change, not the one it happens to. Start my Senior Algorithmic Trading Engineer plan, free What happens next: a free account, then we build your plan as you set up. No card. Build your plan, see your roadmap and meet the twelve tutors matched to you. All free. When you're ready to start learning, it's £70 a month, billed monthly. Cancel any time and billing stops.