• Lead the architectural design, evolution, and scaling of our distributed backend microservices and machine learning platforms. • Establish, champion, and enforce engineering best practices across the organization, including rigorous code reviews, automated testing, design docs, and security protocols. • Mentor and coach senior engineers, fostering a culture of technical curiosity, continuous learning, and high execution velocity. • Design and implement high-performance, resilient, and secure cloud-native solutions using Python and modern web application frameworks. • Architect and optimize data layers, ensuring database designs (SQL and NoSQL) are tuned for high throughput, low latency, and long-term scalability. • Drive the containerization and orchestration strategy using Docker and Kubernetes to ensure seamless deployments and efficient resource utilization. • Build and maintain robust MLOps infrastructure to streamline the entire ML lifecycle—from data pipelining and model training to production deployment and monitoring. • Own and secure our AWS cloud infrastructure, optimizing complex networking setups including VPCs, DNS, ingress controllers, and service meshes. • Architect end-to-end CI/CD pipelines and DevOps automation to facilitate reliable, friction-free daily deployments. • Cultivate absolute system visibility by implementing comprehensive observability stacks (Datadog, Prometheus, Grafana, OpenSearch/ELK) and distributed tracing.

Role Description TransFICC is hiring a Systems Infrastructure Engineer to provide high-performance services to our customers. We develop an integration service product that enables our clients to have a flexible, hosted service without requiring their internal resources to respond to connectivity challenges across trading venues. You will be joining our SRE team and contributing to TransFICC’s culture of automation. We are a multidisciplinary team covering all aspects of Linux, including: - Physical data centre provisioning - AWS cloud - Networking infrastructure Your mission will be: - Building out the automated provisioning of TransFICC's servers and networks, both in physical environments and Cloud (i.e., AWS) - Contributing to our first-class Infrastructure-As-Code ecosystem based on Ansible, Terraform, and other high-level programming languages (e.g., Python, Bash) - Evolving our Continuous Delivery pipeline for provisioning servers and switches, and deploying software - Managing Linux builds and configuration across all physical and virtual hardware - Interacting with hardware vendors, data centre hardware specialist teams, telecom providers, and financial institutions - Optimising hardware and software server builds for low-latency and high-performance trading activities - Planning work in data centres Qualifications - Need to know how to code; basic programming in your language of choice is required - Experience with a software automation tool like Ansible - High degree of Linux administration is essential - Experience as a systems administrator - Reasonable understanding of systems, networks, and security - Constructive, open-minded, and self-motivated - Appreciate autonomy and be able to take the initiative - Experience managing 3rd parties via email and phone - Ability to work with other teams, including developers, customer support, and sales Requirements - Authentication Protocols (i.e., SAML, OAuth2, OpenID, Kerberos) - Microsoft/Azure Active Directory - Database HA - Clustering/replication (e.g., Postgres) - Happy to provide desktop support for MacOS, Windows, and Linux laptops Benefits - Salary: Up to £110,000 + Shares + Benefits - Remote First; office location Moorgate, London (flexible remote working locations within UK/Europe) - Full-time working hours (9-5 UK)

Role Description Seed-X is looking for a visionary Principal / Staff Software Engineer to own, architect, and elevate our backend ecosystems, machine learning infrastructure, and cloud platforms. In this dual-impact role, you will act as a premier individual contributor and a technical beacon for the engineering team. You will bridge the gap between advanced backend engineering, scalable MLOps, and robust cloud infrastructure, ensuring our production-grade platforms are highly available, observable, secure, and built to scale. If you thrive on solving complex distributed systems problems and setting the gold standard for engineering excellence, we want you on board. Key Responsibilities - Technical Leadership & Architecture - Lead the architectural design, evolution, and scaling of our distributed backend microservices and machine learning platforms. - Establish, champion, and enforce engineering best practices across the organization, including rigorous code reviews, automated testing, design docs, and security protocols. - Mentor and coach senior engineers, fostering a culture of technical curiosity, continuous learning, and high execution velocity. - Backend & Infrastructure Engineering - Design and implement high-performance, resilient, and secure cloud-native solutions using Python and modern web application frameworks. - Architect and optimize data layers, ensuring database designs (SQL and NoSQL) are tuned for high throughput, low latency, and long-term scalability. - Drive the containerization and orchestration strategy using Docker and Kubernetes to ensure seamless deployments and efficient resource utilization. - MLOps & Cloud Operations - Build and maintain robust MLOps infrastructure to streamline the entire ML lifecycle—from data pipelining and model training to production deployment and monitoring. - Own and secure our AWS cloud infrastructure, optimizing complex networking setups including VPCs, DNS, ingress controllers, and service meshes. - Architect end-to-end CI/CD pipelines and DevOps automation to facilitate reliable, friction-free daily deployments. - Cultivate absolute system visibility by implementing comprehensive observability stacks (Datadog, Prometheus, Grafana, OpenSearch/ELK) and distributed tracing. Qualifications - Experience: 9+ years of professional software engineering experience, with at least 3+ years spent operating at a Staff, Principal, or equivalent technical leadership capacity. - Track Record: Demonstrated success in designing and operating large-scale distributed cloud systems from the ground up. - Mindset: A strong sense of ownership, a passion for automation, and the communication skills required to translate complex technical visions into actionable team execution. - Education: Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical field (or equivalent practical experience). Requirements - Core Development: Mastery of Python and deep experience building enterprise-grade backend systems and web applications. - Distributed Systems: Proven track record in microservices architecture, API design, asynchronous event-driven patterns, and system scalability. - Cloud & Networking: Deep, hands-on expertise with AWS cloud infrastructure, networking configurations (VPCs, DNS, Ingress, Service Mesh), and infrastructure as code. - Containers & Orchestration: Production-level mastery of Docker and Kubernetes for scaling and managing containerized workloads. - Data Management: Strong proficiency in database design, query optimization, and handling complex data lifecycles. - MLOps Foundations: Experience building or integrating machine learning infrastructure, model deployment pipelines, and ML feature stores. - Observability & DevOps: Expert knowledge in deploying logging, metrics, and tracing stacks (Datadog, Prometheus, Grafana, ELK) alongside bulletproof CI/CD pipelines. Benefits - Competitive salary and equity packages. - The opportunity to significantly shape the technical trajectory of an innovative, growing company. - Remote work and flexibility. - Budget for continuous learning, conferences, and professional development.

• Define and execute supply planning strategies • Drive capacity planning from end to end • Work closely with Product and Engineering • Engage with vendors and OEM partners • Collaborate with Procurement to build sourcing strategies • Engage Infrastructure Operations and Data Center teams • Build and continuously refine demand forecasting models • Define utilization thresholds and refresh cycles • Identify and implement tools, methodologies, and process improvements • Deliver data-driven capacity insights and concrete recommendations to senior leadership