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Full-Stack Engineer (AI Focused) – London (On-site) We’re working with an early-stage start-up, who are building an AI-powered workspace for finance and strategy professionals, to hire multiple Full-Stack Engineers. This is a unique opportunity to join a YC-founded business backed by top-tier VCs, and a healthy runway. The founders are serial entrepreneurs with multiple successful exits, and they’re now building what they believe will be the leading AI application platform for enterprise. The role As a Full-Stack Engineer, you’ll have broad ownership across the stack: Developing frontend applications (React/Next.js). Building scalable backend services and APIs (Python/Django/FastAPI preferred). Designing and deploying AI-powered features, including multi-agent systems, RAG pipelines, and model fine-tuning. Contributing to infrastructure, DevOps, and CI/CD. Delivering production-grade AI applications used by some of the world’s biggest enterprises. This is a chance to shape real-world AI systems that are already transforming how finance and consulting professionals work. What they’re looking for 5+ years’ experience as a professional software engineer. Solid backend skills (Python preferred) and frontend experience (React/Next.js) Experience with cloud platforms (AWS/GCP/Azure), Docker/Kubernetes, and CI/CD. Background in deploying AI/LLM applications in production. Familiarity with RAG pipelines, agent orchestration, fine-tuning, and evaluation frameworks. Comfortable in a fast-moving, high-growth environment. What’s on offer Competitive salary + meaningful equity (discussed later in the process). A chance to work on cutting-edge applied AI with enterprise-scale impact. Fast-paced, ambitious culture with global reach. If you’re ready to make your defining career move in AI, apply now!

Our startup client are building an agentic AI platform to automate rental workflows end-to-end and transform a massive, outdated industry. Backed by recent pre-seed funding, they’re looking for a talented software engineer to join their team. Why apply? You’re ready to build production-grade systems with GCP, Kubernetes, Node.js (NestJS), and Angular (or eager to learn fast). You care about best practices: testing, observability, DevOps. You thrive in a focused, high-intensity team and want to tackle hard technical challenges. What you’ll do: Build and maintain Node.js (NestJS) microservices on Kubernetes (GCP). Work with AI engineers and LLMs to ship first-of-its-kind products. Contribute across the stack: Angular frontend, Node.js backend, GCP infrastructure. Manage fintech integrations (payments, KYC/AML). Drive impact with high autonomy in a product-led team. Compensation & growth: Competitive salary + meaningful equity. Performance-based cash & equity rewards. Clear path for rapid progression. If you’re excited to build production-grade AI systems and shape the future of a massive industry, apply today!

Our client in the Life Science industry is start up in stealth mode backed by great funding. They are seeking a Principal Data Engineer to lead the data and infrastructure systems powering the foundation model transforming drug development. Requirements: Principal-level data engineering experience in life sciences is essential. End-to-end ownership of data workflows is required, from extraction and transformation to clean Parquet outputs for machine learning teams. Hands-on familiarity with genomics data is needed, including raw FASTQ files and outputs from Illumina sequencers. Experience with metabolomics data is important, particularly untargeted mass spectrometry. Close collaboration with wet lab teams is expected, with practical understanding of assays and protocol development. Cloud data infrastructure must be set up from scratch, including compute, storage, networking, and access controls. Strong Python and SQL skills are required, along with sound practices for data modeling, data quality, lineage, and monitoring. Reliable, repeatable pipelines should be built with testing, version control, and clear documentation. Preference: Experience building data lakes or lakehouses and automating batch workflows (for example, with Airflow) is beneficial. Familiarity with NGS pipelines such as quality control, alignment or assembly, and variant calling, as well as mass spectrometry data analysis, is advantageous. Use of Infrastructure as Code (such as Terraform), containerization (Docker), and CI/CD for deploying data systems is desirable. Prior 0-to-1 startup experience and close collaboration with machine learning and biology teams are strong positives. Why Join Design and build the cloud infrastructure and data pipelines that power distributed ML training and scalable biological data workflows—without legacy constraints. Work with first-of-their-kind, multi-modal datasets to support foundation model training at AlphaFold scale—this is a builder role with deep technical ownership. Join as a founding member of the engineering team with significant equity and end-to-end system ownership See your work directly enable drug discoveries that will impact millions, collaborating with world-leading scientists in microbiome research and machine learning. Location: London - 3 days onsiteSalary: £ 80 000 - £ 120 000 plus equity