Senior Software Engineer building a multimodal AI data fusion platform for Defence and Security using Python, distributed systems, container orchestration, and agent frameworks across cloud, edge, on-premise, and air-gapped environments. You'll design core platform components, develop AI orchestration systems, define deployment architectures, and influence technical direction across the organization. Requires 7+ years shipping production software, systems design expertise, and experience architecting multimodal data systems.

You will work with AWS, Kubernetes, Terraform, Python, Java or Scala, and AI-driven development tools (Claude, LLMs). You will build and maintain the distributed-compute and data-science platform that powers Macquarie's trading and analytics workflows, collaborating with quantitative analysts and trading desks.

Use Python, Azure, Docker, Kubernetes, Apache Airflow, and GitHub Actions to build scalable ETL pipelines, financial data pipelines, and cloud-native infrastructure. This front-office role is at a systematic equity hedge fund modernising its quantitative research platform, working directly with portfolio managers and researchers. Experience with S&P Xpressfeed, Snowflake, Bloomberg, MSCI Barra, Databricks, and LLMs is advantageous.

Rebuild data infrastructure for a market-neutral systematic equities fund using Python, Microsoft Azure, Docker, Azure Kubernetes, Apache Airflow, and GitHub Actions for CI/CD. Work on ETL pipelines, vendor integration, and cloud-based research platforms, with relevant experience in Snowflake, Bloomberg, MSCI Barra, or Databricks. The role spans data engineering and quantitative development to transform financial data into investment signals.

You'll build scalable data infrastructure for AI applications using Python, SQL, Spark, dbt, LangChain, and cloud platforms (AWS, Azure, GCP), working with data pipelines, embeddings, vector search, and LLMOps tools like Terraform and LangSmith. QuantumBlack, McKinsey's AI division, develops next-generation AI systems and enterprise solutions for clients across industries. You'll collaborate with Data Scientists and ML Engineers in cross-functional Agile teams based in London, supporting the firm's AI adoption and complex problem-solving at scale.

Boston Consulting Group★4.2 (537)· London

Uses Tableau, Claude, and ChatGPT for recruitment analytics and insights. Leads global reporting and strategy for BCG X, the tech unit of Boston Consulting Group, a management consulting firm, to improve hiring and operational excellence. Team scope is not stated.

EXL Service★3.7 (2k)· London

You will work with Python, FastAPI, LLM frameworks (prompt engineering, RAG, agentic systems), and cloud AI platforms (Azure OpenAI/AWS Bedrock/Claude) on Kubernetes. As a Sr. AI Architect & Client Partner at EXL, a data and AI services company, you will design and deliver production-grade Generative and Agentic AI systems for enterprise clients, converting ambiguous mandates into secure, scalable solutions while shaping deals and reusable IP.

Verkada★3.1 (18)· London

Use Gumloop, Claude, Workato, Retool, APIs, and lightweight code alongside Salesforce and Marketo to build AI-powered marketing automations and agents. You will lead campaign operations for Verkada’s Marketing team, connecting workflows with data warehouses and internal resources to reduce repetitive work and improve execution.

Verkada★3.1 (18)· London

You will work with Gumloop, Claude, Workato, Retool, APIs, Salesforce, Marketo, data warehouses, and optionally SQL/Python/TypeScript. The Marketing Operations team builds AI-powered automations, agents, and campaign infrastructure to streamline demand generation and improve marketing execution.

MAREX★3.2 (6)· London

Design and implement resilient data ingestion, orchestration, and provisioning using APIs, event streaming, CI/CD, and infrastructure-as-code for Marex's enterprise data products. This role supports the firm's global financial services platform by delivering trusted, reusable data assets and integration capabilities for operational, regulatory, and analytical use cases.

Use Tableau, Claude, and ChatGPT to build dashboards, analyse data, and drive recruitment insights. As BCG X's Global TA Strategy and Analytics Manager, you own recruitment reporting and lead strategic programmes that enhance hiring quality and operational excellence across the function.

This role develops generative AI applications using Java, Python, React or Angular, LangChain, LlamaIndex, Hugging Face, Docker, Kubernetes, and AWS, with tools like GitHub Copilot. You will build scalable, AI-powered solutions for Citi’s global finance operations.

Python, SQL, Spark, Airflow, and AWS are used to build and maintain data pipelines, including ELT/ETL, for the Search and AI Platform powering Scopus, ScienceDirect, and AI-driven research solutions. AI-assisted tools like Claude Code, Copilot, or Codex are part of the workflow.

Capgemini★3.7 (11k)· London

You will work with Python, LLMs (GPT, Claude, Gemini, Llama, Mistral), RAG pipelines, vector databases (Pinecone, FAISS, ChromaDB, Weaviate, Milvus), and frameworks like LangChain, LangGraph, Semantic Kernel, CrewAI, or AutoGen. You will design, develop, and deploy generative AI applications for enterprise use cases at Capgemini, an AI-powered global business and technology transformation partner.

You'll work with Python, FastAPI, PostgreSQL, AWS services (RDS, S3, Redis, MongoDB), and AI-assisted development tools to design and optimize databases, build data-integration pipelines, and develop scalable APIs. The role owns the data layer powering M+C Saatchi World Services' platform, handling time-series, geospatial, and relational data across complex multi-source systems for a communications agency serving governments and international organizations. This is a full-time hybrid position in London, reporting to backend and data teams.

Use Python, Azure, Docker, Kubernetes, Apache Airflow, and GitHub Actions to modernize a systematic equity hedge fund’s quantitative research and engineering platform. You will build scalable ETL pipelines, cloud-native infrastructure, and research-ready datasets, working directly with portfolio managers and quantitative researchers.

Senior KDB developer working with kdb+, q, time-series databases, Unix/Linux, and scripting; also complementary tools like Python, cloud platforms (AWS/Azure/GCP), and AI development tools (GitHub Copilot, Claude). The role designs enterprise-scale kdb+ architectures and builds real-time/historical market-data solutions for a financial technology firm focused on market data and analytics platforms.

Work with Databricks, Azure, Python/PySpark, Git, CI/CD, and AI coding tools (GitHub Copilot, Cursor, Claude Code) to build and scale data pipelines for an investment management firm. You will design governance, monitoring, and security frameworks for a cloud data lakehouse while optimizing performance and producing production workloads. This is a key hire on a small, high-impact team.

You’ll work with SQL, Snowflake, dbt, Fivetran, and Claude to build the analytical foundation for Lendable’s US Loans team. You will own and improve data models supporting lending decisions, pricing, portfolio analysis, and investor reporting, and drive dbt model development to streamline insight generation.

Lead a team building enterprise-scale AI platforms for a top-tier hedge fund, using Python, C#, Scala, Java or Go; LangChain, LlamaIndex, Claude Code, Aider; MLflow; SQL, Pandas, Polars, Snowflake, Vector Databases; Docker, Kubernetes, Helm, Flux; and Airflow, Dagster, DBT. You'll architect multi-agent systems, orchestration frameworks, and production AI applications to transform investment workflows.

You'll work with SQL, Snowflake, dbt, Fivetran and Claude to build the analytical foundation for Lendable's US Loans team, improving how data is structured, transformed, and consumed with analysts, product teams, and engineers.

You'll work with SQL, Python, dbt, Snowflake, Lightdash/Looker, Streamlit, and AI/agentic automation. As part of the Regional Financials Marketing Analytics team at a global money-movement company, you'll build and automate the technical infrastructure that explains marketing growth drivers and identifies strategic opportunities.

You'll work with SQL, Python, R, dbt, Hex/Looker, Statsig/Eppo, and Amplitude/Mixpanel. Embedded in a small, fast-moving team building a new AI-native product inside Goodnotes, you'll define success metrics, build experimentation practice, and enable self-serve analytics.

You will work with Azure (AI Foundry, AI Search, Cosmos DB, API Management, observability), Langfuse, Datadog, LiteLLM, MCP gateways, contemporary AI models, agent harnesses (Claude Code, Codex, GitHub Copilot), OpenTelemetry, LangChain, LangGraph, and Azure document-processing services. The team builds and experiments with AI agents and retrieval-augmented generation (RAG) systems at LSEG, a global financial markets infrastructure and data company. The role is at the Manager career stage.

You'll work with Python, PyTorch, Scikit-learn, and Hugging Face, building RAG pipelines, agentic AI systems, and MLOps pipelines while using AI coding assistants like Claude Code or Codex. You'll design and deploy production-grade machine learning and generative AI solutions for a technology company investing heavily in advanced AI and agentic systems.