You’ll use Python, Docker, Kubernetes, CI/CD tools, cloud platforms (AWS, Azure, GCP), and IaC tools like Terraform or Ansible, with AI frameworks such as PyTorch or TensorFlow. As an Applied AI Engineer at Mistral, you’ll onboard customers and deploy production AI solutions across infrastructure, back-end, and front-end. No team size is stated.

Work with Python, TypeScript, LLMs (Claude, Gemini), agent frameworks, RAG, vector databases, and MCP-based tools. The team builds enterprise-grade AI infrastructure

Python and/or C#/.NET, with experience using LLM APIs, retrieval-augmented generation (RAG), prompt engineering, and agent orchestration patterns. This director-level role defines and builds WTW’s enterprise-wide AI engineering capability, creating shared frameworks, reusable patterns, and reference implementations for production-grade generative AI and agentic solutions across the company.

Quantiphi★3.3 (60)· London

Architect MLOps strategy and implement enterprise-grade ML/LLM pipelines using AWS SageMaker, EKS, Lambda, API Gateway, and CI/CD tools. Design hybrid MLOps/LLMOps workflows with governance, monitoring, and container-orchestrated platforms. Lead cross-functional delivery for an AI-first digital engineering company serving Fortune 1000 clients.

Work with Cisco and Arista platforms, including VxLAN, EVPN, Meraki, and traditional enterprise networking, plus automation and infrastructure as code. You'll engineer enterprise network solutions for NatWest Digital X, ensuring security, resilience, and operational requirements.

Design, build, and operate cloud infrastructure on AWS, Azure, or GCP using Terraform, Kubernetes, Docker, CI/CD pipelines (GitHub Actions, Azure DevOps), and scripting (Python, Bash, PowerShell). The role delivers secure, scalable platforms for enterprise applications and digital services, partnering with software, security, and architecture teams.

Work with Azure, AWS, Terraform, Kubernetes, Docker, Python, Go, and CI/CD pipelines to architect and operate secure, scalable cloud platforms for AI products at LSEG. This individual-contributor role owns the technical direction of cloud infrastructure, delivery pipelines, and operational capabilities, providing functional leadership across teams.

Develop software using Java, C#, Python, JavaScript, TypeScript, Go, RESTful APIs, microservices, SQL databases (PostgreSQL, MySQL, etc.), MongoDB, cloud platforms (AWS, Azure, GCP), Docker, Kubernetes, and CI/CD tools. This role builds and maintains enterprise applications and business-critical services for Elite Global Logistics, a logistics firm.

Develop software solutions using Java, Spring, and Spring Boot, building microservices and REST APIs in a cloud or hybrid environment. Work with databases like MS SQL Server or Oracle, and tools such as Databricks, Terraform, and AWS services including SQS and SNS. The role is within a team creating enterprise-scale applications, leveraging AI-assisted development tools to improve code quality and delivery speed.

WTW★3.6 (1.7k)· London

This role shapes WTW’s enterprise-wide AI engineering capability, defining technical direction for production-grade generative AI and agentic systems. You will work with Microsoft Foundry, Copilot Studio, Lyzr, Anthropic Claude, Moveworks, LLM/agent frameworks, and Model Context Protocol while building RAG pipelines, LLMOps practices, and governed integration patterns.

LSEG★3.7 (403)· London

Work with Azure, AWS, Terraform, Bicep, CloudFormation, Ansible, Docker, Kubernetes, Python, Bash, PowerShell, Go, CI/CD, and generative AI tools. Build scalable AI products and platforms by owning cloud infrastructure, delivery pipelines, and operational engineering. This individual contributor role provides functional leadership, guiding engineers without direct reports.

You will work with Python, Go, or PowerShell; REST APIs for Slack, Google Workspace, and Okta; SaaS security tools like AppOmni or Adaptive Shield; and Google/Atlassian stacks, IAM, DLP, and data governance systems. You will safeguard corporate identity systems, sensitive data, and physical workspaces for a team advancing AI-driven drug discovery.

Lead engineering teams using AWS, GCP, or Azure, plus JavaScript, Java, or .Net with full-stack frameworks, Agile, CI/CD, and infrastructure-as-code. The role drives digital transformations by delivering enterprise-grade cloud-native applications and bridging client business objectives with technical capabilities.

You will work with AWS, Kubernetes (EKS), Terraform/Pulumi, Python/Go, and Grafana/Prometheus to build and maintain infrastructure and tooling for a cloud-native video intelligence platform deployed across thousands of connected devices. This hands-on role involves scaling AWS and Kubernetes, managing IoT device lifecycles, building CI/CD pipelines, and improving observability across cloud and edge environments.

Work with Python, Flask/FastAPI, PostgreSQL, MySQL, MongoDB, Redis, Docker, Jenkins or GitLab CI/CD, Linux shell scripts, and Git. Build and maintain automation solutions, REST APIs, and tooling for large-scale telecom network operations, supporting 5G and enterprise platform testing and monitoring.

Senior Platform Engineer role working with Azure, Kubernetes (AKS), Terraform, GitHub/GitHub Actions, ArgoCD, Docker, Bash/Shell, and Python. You will design, build, and operate central platform services for the Retail Platform Operations team, enabling development teams with self-service infrastructure and CI/CD automation at Legal & General.

Bloomberg★3.8 (1.1k)· London

You will work with Go and C++ on Vitess, MySQL, MyRocks, and RocksDB, alongside Python for automation and analysis. Your team builds Bloomberg’s distributed OLTP storage platform, operating over 10,000 MySQL shards to serve critical financial data with low latency.

Stanley David and Associates★2.3 (3)· London

Work with Snowflake, GitHub, Octopus Deploy, SQL, Python, PowerShell, Shell scripting, and cloud platforms (Azure, AWS, or GCP). Lead design, implementation, and deployment of cloud-based data platforms, including CI/CD pipelines and ELT/ETL processes. Mentor developers and provide technical leadership across project teams.

EPAM Systems★3.8 (703)· London

You will lead the design and optimization of scalable cloud-native data architectures using Azure Databricks, PySpark, Delta Lake, and Delta Live Tables, with Azure-native services like Data Factory and Synapse, plus CI/CD tools (Terraform, GitHub Actions). The team builds large-scale data platforms and ETL/streaming pipelines following Lakehouse principles, driving modernization and AI initiatives. As tech lead, you mentor engineers and define data strategies.

Bloomberg★3.8 (1.1k)· London

You will work with Go, C++, Python, Vitess, MySQL, MyRocks, RocksDB, and InnoDB. The team builds Bloomberg’s distributed OLTP storage platform, operating over 10,000 MySQL shards to serve critical financial data and building custom read/write APIs. The role covers the entire storage fleet at thousands-of-shards scale.

You will work with AWS, Python, Kafka, Kubernetes, gRPC, Terraform, CloudFormation, Docker, and CI/CD tools like Jenkins or GitHub Actions. AeroVect builds autonomous ground-handling systems for airlines, and you will own the cloud infrastructure and data pipelines that power their real-world deployments.

Work with Python, GitLab CI/CD, Helm, ArgoCD, Terraform, Kubernetes, OpenShift, AWS, Docker, Bash, and Go to build CI/CD pipelines and manage infrastructure as code. This free 16-week course prepares candidates for a DevOps role with one of the company's clients.

Wiz seeks an Expert Backend Engineer to develop and maintain large-scale distributed components powering its cloud and AI security platform. You'll work with Golang, GraphQL, PostgreSQL, Neptune, Docker, Kubernetes across multi-cloud environments (Azure, AWS, GCP, OCI, Alibaba), handling end-to-end development, architectural decisions, and system optimization for a product that scans over 230 billion files daily.

Design, develop, and optimize scalable data solutions using Snowflake, GitHub, and Octopus Deploy, with CI/CD pipelines and cloud platforms (Azure, AWS, GCP). This role leads the design, implementation, and deployment of modern cloud-based data platforms, including ELT/ETL pipelines and secure automated deployments.

A Core AI Engineer at LSEG designs, develops, and deploys enterprise-grade AI products and services, building agentic workflows, RAG solutions, and scalable integrations with LLMs and vector databases. The role leads technical implementation across AI initiatives, mentoring engineers and defining solution architecture. The team is transforming how LSEG operates by using AI to improve service resilience, automate workflows, and accelerate engineering productivity.