Role Description We are building the next generation. Laioutr, the Agentic Frontend Management Platform that lets merchants worldwide ship and run high-quality storefronts in hours, not months. This role is different from a classic developer job. You do not just write code, you direct AI to build software at a speed a solo engineer could never reach alone. TypeScript is your native language. You love shipping, you love the craft, and you want your fingerprints on the product real customers use every day. We are not hiring hands. We are hiring a builder who thinks like an owner. - Ship features across our platform end to end, from data layer to storefront, using AI as your primary accelerator to move faster without dropping quality. - Build and maintain third-party integrations inside the platform. - Unify different APIs (GraphQL, REST) into a single, frontend-optimized API. - Develop and maintain Nuxt modules and internal npm packages in a monorepo, including the build tooling and publishing pipeline around them. - Evolve our Next.js application together with tRPC and Supabase. - Build frontend components in Vue and React and wire them to real data sources. - Shape system architecture with the team and make the calls that keep us fast six months from now. - Turn AI from a novelty into a daily engineering habit: prompt it well, review it hard, and keep raising the bar on what one engineer can ship. Qualifications - You love TypeScript more than your own mother. Strong command of complex generic types, and you enjoy designing clean TypeScript APIs and type systems. - You treat AI as a force multiplier. You already build with AI tooling and you have opinions on how to get real, production-grade output from it, not just demos. - Solid experience building Nuxt APIs and integrating them into frontend applications, including Pinia for state management. - Confident with Vue.js and comfortable in React. - You handle APIs (GraphQL, REST) in your sleep: consuming them, designing them, unifying them. - Experience building custom Nuxt modules is a strong plus. - Familiar with build tooling and semantic versioning. Your own experience publishing npm packages is a plus. - Hands-on with CI/CD pipelines and Vite. Turborepo experience is a bonus. - Completed IT degree or equivalent training, plus real-world experience in TypeScript and JavaScript. - Nice to have: experience with e-commerce systems like Shopware or Shopify. - Fluent German or English, written and spoken. Benefits - Remote work, from anywhere in Germany - Modern hardware - Flexible working hours Company Description Our company is fully remote, empowering the team to work from anywhere. We operate on trust, flexibility, and accountability to create a collaborative and productive environment, no matter the location. - Flexible Hours, Clear Outcomes: We focus on results—not timezones. Everyone works when they're most productive, as long as goals and teamwork are maintained. - Async First: We use tools like Slack, Notion, and Loom to reduce meetings and support deep work across time zones. - Regular Syncs: We avoid micromanagement, but stay connected via stand-ups, team check-ins, and monthly all-hands. - Clear Documentation: All tasks and decisions are documented for transparency and easy access. - Digital-First Culture: From hardware stipends to wellness support, we provide what’s needed to thrive remotely. - Trust & Autonomy: We hire self-starters who thrive independently but contribute actively to team success.

• Design and own end-to-end AI solution architectures, covering data pipelines, AI services, integrations, and infrastructure requirements. • Define camera setups, imaging requirements, and hardware specifications for computer vision use cases. • Coordinate installations and integrations with internal teams. • Collaborate with Digital, IT Infrastructure, Software Engineering, and Master Data teams to ensure scalable and maintainable solutions. • Develop and deploy AI models on edge devices where low latency or offline processing is required. • Create and optimize conversational AI for natural language interactions and improved user experiences. • Continuously explore and incorporate emerging AI/ML technologies to enhance the efficiency and scalability of solutions. • Monitor model performance and conduct regular evaluations to maintain accuracy and reliability. • Contribute to bi-weekly brainstorming and team innovation sessions to propose new ideas and solutions.

Role Description We are looking for a talented Senior AI Engineer to join a brand new delivery squad focused on solving new client problems in 4-week cycles. Each project is designed to produce a working pilot that demonstrates clear value, not a polished long-term system. You’ll work in a 4-person team (AI Engineer, Product Manager, Data Scientist, Principal for AI Engineering), using AI coding tools (e.g. Claude Code) to reduce build time and get solutions into a usable state quickly. The role includes direct interaction with clients, where you’ll help shape solutions and explain technical decisions. - Experiment with POCs to find solutions for real-world problems using Large Language Models. - Collaborate on AI-driven projects, working alongside engineers, product managers and Data Scientists while maintaining clear documentation. - Build Agentic solutions with LangGraph/ADK. - Familiar with different multi agent system patterns. - Build and deploy LLM-based solutions using RAG. - Familiar with different types of databases: Relational, Vector, Graph etc. - Design and optimise APIs using Python and FastAPI to serve AI solutions. - Familiar with GCP ecosystem and Cloudrun. - Build and optimise data pipelines for vector search and knowledge retrieval using Vector databases and embedding models. Qualifications - Experience building production LLM systems used by clients/customers. - Background in Software Engineering with Python. - Solid understanding of the Python standard library and modern Python coding, testing, debugging and automation techniques. - Hands-on experience building solutions using LLMs and Agentic architectures with ADK, LlamaIndex, or LangGraph. - Experience using AI-Assisted coding tools (such as Claude Code) to help accelerate development cycles. - Ability to deliver usable outputs within 4 weeks. - Working with vector databases for embedding and indexing. - Strong experience with cloud platforms. - Strong experience with API design and frameworks like FastAPI or Flask. - Solid experience with relational databases and SQL. - Interest in expanding your knowledge into GenAI and machine learning. - Excellent communication skills and the ability to work well in a collaborative team environment. Requirements - Nice to have: Strong experience with GCP. - Experience with Graph databases. - Experience in bringing data-intensive projects into production. - Experience with CI/CD pipelines. Benefits - Remote Contract (UK Candidates only). - Ideal start date: ASAP. - Contract Duration: 6 Months. - Outside IR35. - Rate: £500-600 p/d. - Work Environment: Fully Remote in the UK. Company Description Elsewhen, a London-based consultancy, designs and builds technology solutions for clients like Spotify, Google, Inmarsat, and Zego. Over the past decade, we have built a workplace prioritising impact, drive, and friendliness. We value outcomes over hours and agility over rigid processes. Our Commitment to Diversity: Diverse thoughts, backgrounds, and perspectives create stronger teams and better technology. We welcome everyone, regardless of culture, appearance, or perspective, fostering individuality. We empower our team to challenge norms, grow ideas, and produce their best work.

• Build and maintain end-to-end deployment pipelines for AI-powered applications, including artifact builds, environment promotion, rollback, and observability hooks. • Stand up and operate the runtime and lifecycle infrastructure for production agents, including deployment, versioning, monitoring, rate-limiting, and retirement. • Own how the organization provisions, rotates, scopes, and meters access to model provider APIs (Anthropic, OpenAI, and others). • Build evals into the CI/CD pipeline so no agent or LLM-powered service ships without passing a defined eval bar. • Stand up self-hosted inference for workloads where managed APIs aren't the right fit. • Design and build the shared developer harness that every AI-powered service uses. • Partner with finance on cost visibility, including token accounting and per-feature cost attribution. • Write documentation, runbooks, and clear interfaces. • Participate in code review and promote collaboration and best practices.