Future Tech Jobs
Future Tech Jobs
We’re currently seeking a Principal Developer Technology Engineer, Artificial Intelligence. Would you enjoy researching parallel algorithms to accelerate AI workloads on advanced computer architectures? Do you find it rewarding to identify and eliminate system bottlenecks to achieve the best possible...
As a Senior HPC DevOps Engineer, you will design, implement, and maintain large-scale HPC and AI clusters, focusing on state-of-the-art monitoring, logging, and alerting systems. You will work closely with HPC, OS, GPU compute, and systems specialists to architect and develop performance platforms, streamline CI/CD pipelines, and automate complex networking and deployment processes.
This role involves leading large-scale training of video foundation models for Wayve's Gaia system, which functions as a predictive world model for autonomous driving. The engineer will drive architectural innovation, improve synthetic scenario generation, and collaborate across research and engineering teams to enhance model capabilities. It is a senior technical leadership position focused on advancing the core AI infrastructure behind embodied driving intelligence.
This role involves developing embedded software platforms that interface with automotive hardware and Wayve’s AI driving models. The engineer will create abstractions and APIs to enable consistent deployment of autonomous vehicle software across different platforms, working on systems like Linux and QNX while minimizing platform-specific code. The position emphasizes performance, reliability, and close collaboration with hardware and software teams to advance scalable, production-ready AV technology.
This role involves designing and building scalable data pipelines and models in Snowflake to support investment decision-making and regulatory reporting. The engineer will work with complex financial and time-series data, integrate market data feeds, and contribute to a modern cloud data platform enhanced by AI-assisted development tools. Collaboration with technical teams and business stakeholders is key to delivering robust data solutions in a transformational environment.
This role involves designing and deploying AI-powered applications using Large Language Models and Generative AI technologies within a modern financial services environment. You'll build prompt engineering frameworks, retrieval-based systems, and scalable AI workflows while collaborating with engineering and product teams. The position emphasizes responsible AI practices, innovation in cloud-native environments, and shaping the organization's AI strategy.
This role involves designing and building end-to-end AI-native applications using cutting-edge technologies like Large Language Models, agentic AI, and multimodal frameworks. The engineer will develop production-ready AI solutions, including RAG architectures, vector search, and agent orchestration, while working across full-stack environments with Python, TypeScript, and modern front-ends. The position is embedded in a financial services context, focusing on delivering scalable, enterprise-grade AI systems that solve real business problems.
This role involves leading the strategic development and delivery of AI transformation programmes for enterprise clients in regulated sectors. The AI Practice Lead will define technical and business strategies, drive innovation in Generative AI and data platforms, and mentor cross-functional teams. Key responsibilities include shaping AI roadmaps, leading high-impact client engagements, and building scalable, industry-specific solutions.
This role involves designing and building AI-powered products and platforms using Golang within Citi's high-growth AI Product & Platform team. You'll develop scalable backend services and cloud-native microservices, collaborate with AI specialists, and contribute to developer tools and frameworks. The position emphasizes innovation in distributed systems, generative AI, and modern engineering practices in a start-up-like environment within a global financial institution.
This role involves designing, developing, and maintaining robotics software for autonomous platforms using ROS2, sensor fusion, path planning, and kinematics. You will work closely with multidisciplinary teams to bring robotic systems from prototype to production, focusing on robust real-world solutions.
This role involves designing, developing, and deploying Camunda-based process and decision automation solutions, integrating Java-based microservices, and collaborating with solution architects and business analysts. You will play a key part in defining technical standards, optimizing performance, and mentoring less-experienced engineers.
This role involves leading the development of physics-informed predictive maintenance systems for high-value industrial equipment. You will work directly with major industrial customers to build pipelines that fuse periodic inspection imagery with equipment operating history and physics-based inputs to predict remaining component life, helping operators reduce costly unplanned interventions and optimize asset availability.
As a Principal Machine Learning Engineer, you will lead the design and implementation of large-scale AI systems, providing technical direction and solving complex challenges across multiple projects. You will work closely with business units to ensure solutions are robust, scalable, and aligned with industry standards, while fostering team growth and influencing company strategy.
This role involves leading the development of large-scale graph visualizations in a next-generation UI for a cybersecurity platform. The engineer will work closely with design, backend, and product teams to create intuitive, data-rich visual features using tools like Keylines and D3.js. The position emphasizes mentorship, cross-functional collaboration, and integration within a high-performance engineering culture.
As a Platform Engineer, you will architect and maintain the infrastructure that enables the deployment of world-class AI solutions. You will work closely with the Applied AI team to build and refine data science, MLOps, and deployment tooling, ensuring high performance and seamless integration into diverse client environments.
