Mid-level Software Engineer role using Python, Git, GitHub/GitLab, TDD, unit/automated testing, Unix, and agile frameworks. You will work on Suade’s regtech SaaS platform that automates regulatory reporting, compliance, and financial risk solutions for Tier 1 banks.

Build and scale agentic AI workflows using LLMs, fine-tuning, and production deployment. As the fourth hire at Bead AI, you’ll replace manual audit checklists with real-time autonomous agents for Fortune 500 enterprises.

Lead Platform Engineering for Volta's GPU infrastructure platform, working with KVM, QEMU, Ceph, SPDK, BGP, VXLAN, Kubernetes operators, Go, Python, and Rust. You will manage EMEA teams of 20+ people, own delivery against the roadmap, and act as deputy to the VP. The role covers architecture, reliability, and the boundary between platform software and hardware.

You will work daily with TypeScript, React, and Python across the full DeepEditor stack. The product is an AI-powered performance editing tool for Hollywood studios. As the technical anchor, you will mentor a growing team of fifteen engineers.

You will work with Python and React, standardising backend practices across Engineering (90 engineers) and R&D (40 engineers/researchers) at Synthesia, the leading AI video platform for business. You will lead multi-quarter projects spanning the entire engineering organization.

Sainsbury’s★3.5 (16k)· London

As Engineering Manager in Integration, you'll lead and coach a multi-skilled team building reusable integration kits, common components, and platform services using JAVA. You'll drive CI/CD, observability, and cloud-native services to standardise how integrations are built, deployed, and operated across Sainsbury’s.

You will work with Python, AWS, and Kubernetes supporting the Forward Deployed Engineering team at a pre-seed voice AI startup building infrastructure for emerging markets, processing thousands of daily calls with proprietary speech models.

Build and deploy production-grade agentic systems and RAG pipelines using Python, TypeScript, FastAPI, and React. As a founding engineer, you will lead architectural development of an AI-driven agency model replacing manual workflows with autonomous agents to redefine the global property market.

Build AI-enabled products using Python, TypeScript, Java or Go at a YC-backed AI start-up. Work directly alongside founders to ship customer-facing solutions and shape both product and engineering culture from day one.

Deloitte★3.9 (14k)· London

You will work with Python, NumPy, Pandas, scikit-learn, LangChain, Hugging Face, LlamaIndex, Azure Machine Learning, Foundry, Git, and Agile practices. The team is Deloitte’s Tax Digital Innovation AI & Data Studio, which researches, builds, and delivers analytics and AI-driven solutions for tax and legal clients.

As a founding AI engineer, you will work with LLMs, Python, PostgreSQL, and React/TypeScript to build production-ready algorithms and evaluation pipelines for patent generation. You will lead proprietary algorithm development for Solveintelligence’s AI platform, which transforms the intellectual property landscape for 400+ global enterprise customers like DLA Piper.

Work with Python, SQL, JavaScript/TypeScript, NumPy, Pandas/Polars, visualization libraries, and deep learning frameworks (PyTorch, JAX, or TensorFlow) to design and deploy full-stack data-driven applications and machine learning solutions. You will be embedded with Arsenal's Men’s First Team Analysis department, building tools that directly support coaching and analysis workflows.

You will work with LLMs, chain-of-thought prompting, RAG architectures, multi-agent tool use, Python, and FastAPI to build cognitive systems. The Science team designs memory and decision-making frameworks to create synthetic populations for behavioral prediction.

Design and evolve multi-agent systems and LLM pipelines on AWS Bedrock using LangGraph, Strands, Python, and frameworks like CrewAI. You will architect agent topologies, manage cloud infrastructure (ECS Fargate, Lambda, Step Functions), and build evaluation frameworks for AMPLIFYR’s AI-powered brand analytics platform.

You will work with Python, Node.js, PyTorch, OpenAI/Anthropic/open-source LLMs, SQL & NoSQL, Kubernetes, and Docker. You own the inference and orchestration layer for a proactive smart assistant that handles multi-step reasoning, tool calls, and long-running workflows, turning model capabilities into stable, production-grade APIs.