Use SystemVerilog, UVM, and Python to verify complex silicon for next-generation AI compute hardware. Develop reusable testbenches, verification plans, functional coverage, and assertions while building automation and influencing verification methodology alongside architecture, RTL, and software teams.

Founding Engineer role at a London AI startup building an agentic platform for civil engineering. You’ll work with Python, GCP (Cloud Run, Pub/Sub, Postgres), React, Terraform, and LLM techniques like RAG and MCP, owning backend architecture and AI integration directly with the CTO.

The intern will use Python (Pandas, NumPy), AWS (Kubernetes, Kafka), APIs, Snowflake, Streamlit, Git, Docker, Helm, and CI/CD. They contribute to front office software tools for real-time trading, market data analytics, and visualization, and work with the commercial trading team to optimize pricing models and trading workflows. The role is with Castleton Commodities International, a global energy commodities merchant and infrastructure investor.

You'll work with Python, modern ML tooling, LLMs, and simulations, owning the AI/ML stack including model selection, fine-tuning, and inference infrastructure. Prior Foundry builds specialized AI agents and inference systems to solve complex global policy problems for the public sector in social science and public policy.

You will work with Python, AWS, and Kubernetes as a Junior Fullstack Engineer at AethexAI Inc. The company builds voice AI infrastructure for emerging markets in Africa and the Middle East, processing thousands of daily calls with proprietary speech models. You will support the Forward Deployed Engineering team on custom integrations and platform fixes for enterprise clients.

Work with Svelte/TypeScript, Python (FastAPI, Django), PostgreSQL, and AWS. Tab is a YC-backed London travel fintech building a payments platform for 100,000+ global tourism businesses, processing thousands of real-time transactions per hour. You will develop features across the stack and collaborate in a tight-knit engineering team.

You will own back-end infrastructure and data strategy at a seed-stage startup building gas sensors and AI that predict food freshness. You will build scalable GCP pipelines, design APIs with Python and FastAPI, and develop full-stack solutions for a mission-driven team of under 20.

You will work with Python, FastAPI, LLMs, RAG architectures, chain-of-thought prompting, and multi-agent tool use. The Science team builds cognitive architectures to create synthetic populations for behavioral prediction, using LLMs to simulate human responses with 95% accuracy.

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.

Senior AI Engineer, 12-month fixed-term, hybrid. Will build production AI solutions using LangChain, LangGraph 1.2.x, DeepAgents, and Azure AI Foundry. Requires expertise in agentic AI, Python, React, and coding agents like Claude Code, with a strong engineering foundation (TDD, design patterns).

Work with Python, LLMs, RAG pipelines, agentic frameworks, and integrations with Google Ads, Meta, and CRMs to build production-grade agentic systems. You will design and deploy AI teammates that automate end-to-end marketing operations—from campaign briefs to paid media analysis—for high-growth brands.

Lead AI Engineer role working hands-on with Python, LLMs, AI agents, RAG, vector databases, and cloud-native distributed systems to design delivery of production AI agents and intelligent workflows. You'll architect scalable AI platforms, mentor engineers, and set engineering standards for a fast-growing AI-native company building enterprise AI products for global industrial organizations within a global software enterprise.

You will work with Python, LangGraph, Strands, CrewAI, and OpenAI/Claude Agent SDKs, plus AWS Bedrock, ECS Fargate, Lambda, and Step Functions to design and evolve multi-agent LLM pipelines. The platform is a production-grade AI-powered brand analytics tool that orchestrates models like GPT, Claude, and Perplexity through a proprietary MCP server.

You'll work with Java, Spring Boot/Micronaut, Kubernetes/Docker, AWS, and Kafka/message-driven architectures, building clean, tested code for NatWest Boxed's technology product. As part of a cross-functional mission team, you'll collaborate with stakeholders, support junior engineers, and act as a subject matter expert.

Work with Svelte, TypeScript, Python (FastAPI/Django), PostgreSQL, and AWS. You'll build and scale a payments platform processing 100 currencies and a discovery engine listing 100,000+ tourism businesses. Join a profitable, lean team of nine as one of the first developers.

You'll use Python, React, and TypeScript to build full-stack applications, backend services, APIs, and microservices. You'll develop real-time trading dashboards, analytics platforms, and data visualizations for an elite FinTech firm supporting trading and operational platforms.

Backend engineers will build low-latency services and APIs in Rust using Tokio, async frameworks, and proc-macros, with cloud infrastructure on Azure and Kubernetes. The role supports a global financial services firm's trading platform, connecting pricing engines, risk systems, and core infrastructure.

You'll work with HTML, CSS, JavaScript/TypeScript, React or Vue, Git, Jira, Figma, automated testing, and AI tools like Claude Enterprise, in an agile model. As an AI-forward web developer embedded in SharkNinja's D2C business, you'll fix bugs from the ticket backlog and bridge Design and Engineering to buildable requirements. No team size is stated.

Talan★3.2 (66)· London

You will design, build and maintain data pipelines using Python, sourcing and processing public and project-specific datasets. Supporting Talan's energy advisory team, you will deliver quantitative analysis on low-carbon technologies and policies to shape industry and investment decisions.

Senior Data Engineer role using SQL, Python, Java, Airflow, dbt, Spark, BigQuery, Snowflake, GCP, AWS, and DOMO. You will design and maintain scalable data pipelines for web analytics, CMS, ad tech, and social media, supporting analytics and reporting across Independent Media’s portfolio of digital news brands.

You will work with SQL, Python, AWS or Azure, Snowflake, Databricks, infrastructure as code, and CI/CD, plus AI tools like RAG, feature stores, and MCP. As a Data Architect on the AI Advisory team, you own data design across client engagements for a CFO advisory firm, defining architecture to support reliable AI, analytics, and reporting.

You will work with Python/R, SQL, pandas, numpy, Robyn, Meridian, PyMC, Bayesian and regression models, and MMM pipelines. You will join the Marketing Analytics team to measure and optimize marketing investments by owning the Marketing Mix Modelling pipeline and translating statistical insights into growth strategies.

Capgemini★3.7 (11k)· London

Work with graph databases (Neo4j, Amazon Neptune, TigerGraph, ArangoDB), Azure AI Search, Elasticsearch, Pinecone, Python, Azure, AWS, Kubernetes, Docker, and CI/CD. Design and implement an enterprise knowledge platform enabling AI agents across Insurance, Payments, and Healthcare domains. Lead platform strategy, enterprise architecture, and cross-functional engineering teams.

The role builds and maintains the automation layer for ElevenLabs' influencer/creator marketing program, covering discovery, onboarding, contracts, content tracking, reporting, invoices, and payment alerts. Tech stack includes Zapier, Make, n8n, Python or JavaScript, APIs, webhooks, SQL, plus integrations with social platforms, CRM, finance, Slack, and e-signature tools.

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.