Monzo★3.5 (108)· London

You will work with LLMs, autonomous agents, RAG, sequence-based architectures, Python, SQL, and Go, developing and deploying machine learning models in production. You’ll lead the design of a human-in-the-loop system that predicts, identifies, and routes customer problems to scale support for Monzo’s banking products across multiple geographies.

You will work with Python, AI coding agents (e.g., Claude Code, Codex), and potentially AWS, Kubernetes, and Temporal. Unitary builds Virtual Agents — AI-powered software workers that automate complex workflows end-to-end in customer tools, focusing on commercial insurance, marketplaces, and primary healthcare.

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.

You'll work with PyTorch, TensorFlow, XGBoost, GPUs, CI/CD and containerisation on the Search & Recommendations team, building production-grade ML systems for personalised recommendations, product ranking and AI-driven styling at ASOS, covering the full lifecycle from experimentation to deployment.

Senior Machine Learning Engineer at ASOS, building production ML systems for personalized outfit recommendations and style discovery. You'll work with deep learning frameworks like PyTorch/TensorFlow, distributed GPU infrastructure, and MLOps practices including CI/CD, containerization, and observability. Collaborate with ML Scientists on batch and real-time models serving millions of customers.

Use deep learning frameworks, distributed computing, GPU-based training, and MLOps to build and deploy batch and real-time ML models. The Search & Recommendations team develops personalised recommendations, product ranking, and AI styling experiences for ASOS's online fashion platform, helping customers discover products.

Work with Java, Python, JavaScript/TypeScript, Go, cloud platforms (AWS, Azure, GCP), CI/CD pipelines, and version control. Guiding the technical direction of BabuSpace’s premium short-term rental marketplace platform for African cities, designing backend architectures, and mentoring engineers.

Salesforce★4.2 (1.5k)· London

Success Architect works with Agentforce, Data Cloud, Salesforce Clouds, and data platforms like Snowflake, Databricks, AWS. They drive customer success by optimizing technical architecture for data unification and AI-driven automation, enabling personalized engagement and real-time decision-making.

FDJ UNITED★4.0 (96)· London

You'll lead a DataOps/MLOps team building an ML platform and data operations capability for FDJ United's Sportsbook, working with AWS, Terraform/CloudFormation, Spark, Kafka, and CI/CD pipelines for end-to-end ML lifecycle management. The role involves establishing best practices, monitoring, and governance while collaborating with Data Engineering, ML Engineering, Quants, and Data Science teams to personalize customer experiences and manage risk.

You'll design and own end-to-end RAG pipelines for payments domain content using Python, Azure Data Factory, Functions, ADLS, CosmosDB, and AI Search, with CI/CD via GitHub Actions and Azure DevOps. RedCompass Labs builds AI-powered payment transformation and financial crime detection solutions, including the RedFlag Accelerator for identifying human trafficking. You'll collaborate with AI engineers and payments experts to turn regulatory documents and handbooks into a reliable retrieval layer for their proprietary multi-agent AI platform.

Senior Data Engineer at Softwire, a UK digital consultancy, working with Python, SQL, Databricks, Snowflake, Fabric, and AWS/Azure/GCP across data architecture, pipeline design, and governance. You'll lead complex data engineering projects for clients across public and private sectors—from healthcare research platforms to energy market infrastructure—while mentoring junior engineers and shaping technical direction on multi-stakeholder engagements.

Wipro★3.8 (17k)· London

You will work with GenAI, LLMs, RAG, agentic frameworks, cloud platforms, DevOps, MLOps, and data governance. As an AI Strategic Advisor, you will define enterprise AI strategy, lead integration of generative and agentic AI, and architect full lifecycle AI initiatives for a global technology consulting firm.

Sell Oracle’s Database Platform across Oracle Cloud Infrastructure (OCI) and multicloud deployments (Azure, Google Cloud, AWS). Use MEDDPICC qualification methodology and work with open-source/cloud-native database alternatives like Postgres and MongoDB. The role focuses on building strategic relationships and closing cloud database opportunities in enterprise accounts.

Design, build and optimise ETL data pipelines using Databricks, PySpark, Python, and SQL for a leading global investment bank. You will work on large-scale enterprise data platforms in a fast-paced financial services environment.

Robert Half★3.9 (231)· London

You’ll develop and enhance Dynamics 365 Sales, Marketing, and Finance & Operations solutions using C#, JavaScript, Power Apps, Power Automate, and optionally Azure Logic Apps or Functions. Working closely with stakeholders, you’ll automate business processes and support integrations and APIs for the company’s digital transformation projects.

This DevOps traineeship covers Linux, Git, Docker, container orchestration, AWS, Azure, Google Cloud, CI/CD, shell scripting, IaC, configuration management, monitoring, networking, and DevSecOps. It provides hands-on experience through realistic projects such as building CI/CD pipelines, deploying applications, managing containers, and automating processes, with no prior experience required.

Design, implement and maintain CI/CD pipelines, deploying and managing cloud infrastructure on AWS and/or Azure with Kubernetes. This role is with Closing Gap, a network placing DevOps engineers into enterprise-scale environments at leading UK technology organisations.

A Senior AI Engineer at Stakemate will use agent frameworks (LangGraph, LlamaIndex, Semantic Kernel, ADK), RAG, Python, cloud services (Azure/GCP/AWS), and SQL to move AI from experiments to production. They will shape the platform and architecture for a live betting product at a fast-growing social sports betting startup.

Microsoft★4.2 (9k)· London

Work with AI and cloud platforms such as Azure ML and OpenAI, applying practices including prompt engineering, retrieval-augmented approaches, model tuning, and CI/CD tooling. As a member of the Frontier Company Engineering team, you will embed within customer teams to build production-ready systems and services that solve complex organizational challenges.

You will work with agent frameworks (LangGraph, LlamaIndex, Semantic Kernel, ADK), RAG pipelines, vector stores, Python, SQL, and a major cloud (Azure AI Foundry, GCP, or AWS). You will take AI agents from proof-of-concept to production within Stakemate’s live sports betting product, setting the governance and standards for the company’s AI estate. Reporting to the CTO, you will shape the platform and architecture as the company scales.

You will work with Python, JavaScript, SQL, Kafka, AWS/Azure, PostgreSQL, SQL Server, ClickHouse, and MongoDB. The team designs and delivers real-time, high-performance trading systems for Energy & Commodities, integrating market data, risk, and front-to-back office workflows.

Java 11+, Spring Boot, microservices, event-driven architecture, Terraform, and cloud platforms (Azure, AWS, or GCP). The team builds post-trade technology solutions including business-critical applications, APIs, client reporting platforms, and web portals for capital markets. You will mentor developers and contribute to architectural decisions.

Work with Microsoft Fabric, Databricks, Azure, Snowflake, Python, Spark, SQL/NoSQL, PowerShell, Azure Data Factory and Azure DevOps to build a Fabric Data Lakehouse for USS’s Investment Management business, implementing scalable ETL/ELT frameworks across a medallion architecture. Share knowledge across a small team of data engineers and collaborate with architects, business stakeholders and data teams.

Work with Microsoft Azure data platforms: Azure Synapse, Azure SQL Server, Azure Data Factory, Azure DevOps, Microsoft Fabric, and OneLake; also uses DBT and Spark. You will modernize core data platforms—ingesting data from MS Dynamics CRM, Finance & Operations, and SAP SuccessFactors—to power analytics, AI-driven insights, and executive decision-making.

You will work with Azure DevOps Pipelines, CI/CD, Atlassian Confluence, Jira, PowerShell, Python, C#, SQL, and cloud deployments to Microsoft Fabric/Synapse/Azure, Snowflake, Power BI, and application security tools. You will help build automation, CI/CD pipelines, and release processes for in-house developed solutions at the Universities Superannuation Scheme pension scheme.