You will use Python, Trio, PyTorch, TensorFlow, JAX, Kubernetes, Rust, C++, and GPU clusters. The team advances reinforcement learning for large language models, improving Claude’s autonomy, coding, and reasoning capabilities.

Work with Google Cloud, Kubernetes, serverless, Terraform, Node.js (TypeScript), and CI/CD pipelines. You'll join the Platform Engineering team at Freetrade, an investing platform, to treat the platform itself as a product—building the foundational infrastructure, observability, and security that Freetrade's own engineers rely on to ship.

Lead Cloud Engineers at Made Tech use AWS, Azure, GCP, Terraform, CloudFormation, Docker, Kubernetes, CI/CD, and languages like Python, Bash, and JavaScript. They help public sector organisations design, implement, and maintain secure, scalable cloud infrastructure. The role includes line managing and mentoring junior colleagues.

You will work with AWS (serverless, Bedrock), TypeScript/JavaScript, Infrastructure-as-Code (Terraform/CDK/CloudFormation), CI/CD, and API design. The Commerce & Technology division designs and builds cloud applications for global brands, specializing in agentic AI platforms and emerging Agentic Commerce standards.

You will work with Python, Go, Rust, Kubernetes (cluster ops, CNI, scheduling), GPU infrastructure, networking (L2/L3, VLANs, overlays), and service architecture. Volta builds a Kubernetes-native GPU compute platform delivering VMs, storage, and networking for AI workloads. You will lead one of the platform engineering capability teams.

Platform engineers design and implement Kubernetes operators and controllers using Python, Go, and Rust. They build and operate large-scale GPU compute infrastructure for AI workloads, spanning compute, networking, storage, and control plane services. Individual teams own different parts of the stack, from managed bare metal through to higher-order platform services.

Build core backend services for DDN’s Infinia AI Data Platform, working with Go, C++, Java, or Python, REST/gRPC APIs, Kubernetes, and microservices in hybrid OnPrem/cloud environments. You will design scalable distributed systems for control-plane orchestration, lifecycle management, and policy enforcement at petabyte scale. This hands-on technical leadership role contributes to API governance, observability, and security across the platform.

You'll work with AWS, GCP, SIEM, EDR, DLP, MDM, Python, Go, and TypeScript. Risk Ledger builds a network for supply-chain organisations to share security maturity and visualise risks. You'll mature security operations, detection, incident response, and cloud security across cloud, endpoint, and SaaS environments.

You will work with Java, Swift, C, Go, Python, and Kubernetes to design and operate highly scalable distributed systems. The team builds Apple’s foundational privacy-focused platform for iCloud, including Advanced Data Protection and Private Cloud Compute, supporting over a billion users.

Blockchain★3.4 (14)· London

Lead a small engineering team building crypto savings and crypto-backed lending products at Blockchain, using Kotlin or Java, Kafka, PostgreSQL, and Redis. You will define technical architecture, design distributed systems, and drive best practices in a hands-on role.

You'll work with TypeScript/Node.js, React, Java/Kotlin, REST APIs, event-driven architectures, AWS, Docker, Kubernetes, Kafka, Keycloak, and observability tooling. You'll lead the PRIIP Cloud platform, WallStreetdocs' cloud-based documentation and reporting system for structured products and derivatives in regulated financial services. No team size is specified.

Senior Software Engineer (L5) contract role on Prime Video Edge Control team. Work with Java, Kotlin, TypeScript, AWS (EC2, NLB, ElastiCache, Lambda, DynamoDB), and AWS CDK to build and operate scalable services for client configuration, push notifications, observability, and a remote AI MCP platform.

Build backend systems with Kotlin or Java, Kafka, PostgreSQL, Redis, and microservices for a crypto savings and crypto-backed lending platform. This hands-on technical lead defines architecture, remains close to the code, and leads a small team of engineers.

Lovable★4.0 (43)· London

Uses Go, Rust, TypeScript; AWS, Azure, Google Cloud, Cloudflare; Kubernetes, Terraform, Temporal, OTEL, CI/CD; PostgreSQL, ClickHouse, Firestore, Spanner, BigQuery. Builds the platform for Lovable Enterprise enabling secure, cloud-agnostic deployment, defining architecture for sandboxing, networking, encryption, identity, and mentoring engineers.

Work with Java (including JDK migration), Kotlin, Python, Kubernetes, ArgoCD, OpenTelemetry, and modern CI/CD pipelines to develop and maintain distributed services for ingesting and processing financial market reference data. You will modernize critical production systems, including a large-scale Java/JDK upgrade programme and improvements to platform reliability and cloud-native infrastructure.

Work with Kubernetes, Docker, Java, Python, Go, JavaScript, Terraform, Ansible, CI/CD, and LLM/AI tooling. You’ll build and operate scalable services for UK government national-security data platforms, own production reliability, and deploy products into air-gapped estates via an in-house continuous-delivery engine.

Dataminr★3.6 (21)· London

Work with Palantir Foundry, Python, Java, SQL, TypeScript/JavaScript, Bash, Go, Docker/Podman, Kubernetes/OpenShift, and Linux. As a Forward Deployed Engineer, you deploy, build on, and operationalize Dataminr’s First Alert inside defense and NATO-aligned customer environments, designing data pipelines, ontologies, and applications on Foundry that fuse real-time intelligence with operational data.

You will work with Unix/Linux, JavaScript, a ticketing system, and networking infrastructure tools. As a Support Engineer on the Global Support Engineering team, you will resolve technical issues with ExtraHop's network detection and response (NDR) product and assist customers with hardware, firmware, and third-party integrations.

HSBC★4.0 (16k)· London

Work with Python, Docker, Kubernetes, Flask/FastAPI, PyTorch/TensorFlow, SQL Server/Postgres, and CI/CD pipelines to build and deploy production-grade ML and GenAI services. You will join the Growth AI programme within HSBC’s Corporate & Institutional Banking Data & Analytics, developing AI applications to identify business opportunities and mitigate client attrition.

NatWest Group★3.7 (1.2k)· London

You'll work with Mainframe hardware (DASD, SAN/FICON, IBM z), automation scripting (Python/Shell), infrastructure as code, GDPS, and CI/CD pipelines. As part of NatWest Digital X, you'll engineer hardware solutions for the Mainframe environment, applying automation to improve products. This technical lead role guides a team but no team size is specified.

The role involves troubleshooting network infrastructure, hardware, firmware, and third-party integrations using a ticketing system and video/phone channels. Preferred technologies include Unix/Linux

Design, configure and manage Mainframe Hardware solutions including DASD, SAN/FICON connectivity, and network infrastructure, using automation scripting (Python or Shell). You will engineer infrastructure-as-code for the Mainframe environment at NatWest Digital X, supporting hardware migrations between IBM z Mainframes and GDPS architectures. This is a technical lead role.

HSBC★4.0 (16k)· London

You'll work with Python, Docker, Kubernetes, PyTorch/TensorFlow, Flask/FastAPI, SQL Server/Postgres, and MLOps/LLMOps pipelines (CI/CD, Git). As part of HSBC's Growth AI programme within CIB Data & Analytics, you'll build and operate production-grade AI services that identify new business opportunities and client attrition risks.

You will work with Java, JavaScript, APIs, Microservices, AWS, CI/CD pipelines, and scripting in Python, Shell, or PowerShell (Docker, Kubernetes, Terraform, or CloudFormation are nice to have). As a Java Support Engineer, you will manage P1–P3 production incidents, perform root cause analysis, support deployments, improve monitoring and automation, and mentor junior engineers.

Work with Python, Apache Airflow, MLflow, Docker, and Kubernetes on AWS to build and maintain production ML pipelines, deployment infrastructure, and monitoring systems for a large-scale clinical monitoring platform. You will own ML pipeline orchestration, model serving, experiment tracking, and observability to support predictive models that identify early signs of clinical deterioration.