Role Description We are looking for a Staff AI Engineer to play a key role in building the core of our AI platform. In this position, you will design and develop production-grade systems that power intelligent automation, agentic workflows, and large-scale retrieval services. This is a highly technical, hands-on role that involves close collaboration with product and platform teams to transform advanced AI concepts into reliable, scalable, and secure solutions used across our enterprise ecosystem. You will also be responsible to: - Design, build, and maintain AI-powered services and APIs, leveraging LLMs (OpenAI, Anthropic, Qwen, OSS models) and custom ML models. - Develop an enterprise-grade agentic framework that enables orchestration, retrieval, and collaboration between multiple AI agents. - Implement and optimize knowledge retrieval systems and agentic search capabilities using vector databases such as Qdrant and ElasticSearch. - Write well-structured, efficient, and testable Python code for production services, experimentation, and internal developer tools. - Build and maintain shared Python libraries and SDKs used across multiple applications and microservices. - Collaborate with cross-functional teams on architecture, internal protocols, and API standards to ensure consistency and reliability across the platform. - Develop and enhance monitoring, validation, and observability for production-grade AI solutions. - Drive the full software development lifecycle - from design and implementation to deployment, monitoring, and continuous improvement. - Identify and resolve performance bottlenecks, reliability issues, and scaling challenges in complex, data-intensive environments. - Participate in code reviews and technical discussions, mentoring other engineers and contributing to a culture of excellence. Qualifications - Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field, or equivalent practical experience. - 7+ years of experience as a Software Engineer, with strong proficiency in Python. - Proven track record of building and maintaining production-grade systems using Python. - Strong understanding of distributed systems, API design, and data-driven architectures. - Experience with relational and non-relational databases (PostgreSQL, Elastic, Qdrant, or similar). - Familiarity with AI/ML system design, including LLM integration and evaluation pipelines. - Knowledge of DevOps and observability practices (CI/CD, monitoring, metrics, and model validation). - Python • FastAPI • LLM APIs (OpenAI, Anthropic, Qwen, OSS) • LiteLLM • Qdrant • PostgreSQL • ElasticSearch • Langfuse • Kubernetes • GitHub Actions • ArgoCD Requirements - Experience working with multiple LLM providers (OpenAI, Anthropic, Qwen, open-source models). - Background in developer platforms or AI infrastructure services. - Familiarity with vector databases, semantic retrieval, and knowledge graph architectures. - Exposure to Langfuse, LiteLLM, LangChain, or similar frameworks. - Experience developing enterprise-scale SaaS or distributed backend systems. - Contributions to open-source projects in Python, AI, or infrastructure engineering. Soft Skills / Personal Characteristics - Excellent communication skills, with the ability to convey complex technical ideas clearly to both technical and non-technical audiences. - Collaborative and proactive approach, comfortable working across teams in a dynamic environment. - Strong analytical and problem-solving abilities, with a focus on continuous improvement and innovation. - Curiosity and a genuine interest in emerging AI technologies and modern backend architectures.

• Gather and analyse business requirements for Conversational AI initiatives • Identify automation opportunities with business stakeholders and clients • Design chatbot and voicebot conversation flows and user journeys • Prepare conversation logic, prompts and process documentation • Configure Conversational AI platforms including Kore.ai, Microsoft Copilot Studio, Dialogflow, Parloa, Cognigy, ElevenLabs or Zowie • Support API integrations between Conversational AI platforms and enterprise systems • Configure NLP models, intents, entities and dialogue management • Support text to speech and voice automation capabilities • Perform functional, NLP and end to end solution testing • Identify issues, propose improvements and support successful implementation • Work closely with Product Owners, Business Analysts, developers and client stakeholders • Prepare solution documentation and implementation artefacts

Role Description The AI Developer / AI Integration Engineer will be responsible for designing, building, and deploying AI-powered solutions across the company. This role bridges modern artificial intelligence capabilities with existing technology platforms — driving operational efficiency, enabling smarter workflows, and shaping how AI is applied across the organization. The ideal candidate is AI-native, a solid developer, and a systems thinker. - Design and deploy AI-powered workflows and automation across internal systems - Integrate LLM APIs (OpenAI, Anthropic, etc.) into operational platforms and internal tooling, with examples including: - Airtable Scripting & AI Automation - Microsoft 365 / Power Platform AI Enhancements - Custom Agent & RAG Pipeline Development - Build and maintain custom AI agents, automation pipelines, and retrieval-augmented generation (RAG) systems - Own the bridge between AI capabilities and the existing technology stack - Evaluate and prototype emerging AI tools for business relevance and operational fit - Collaborate with operations, sales, and leadership teams to identify and prioritize AI opportunities - Contribute to platform development features and maintain clean, well-documented code - Translate AI capabilities for non-technical stakeholders and gather real requirements from business teams - Maintain a running roadmap of AI enhancements tied to business goals and project timelines - Consistently exemplify established best practices, serving as the internal subject matter expert on applied AI Additional Responsibilities: - Provide team or company-wide AI training and education where applicable. - Create & manage technical documentation for all AI systems, integrations, and workflows. Qualifications - AI-Native Mindset: Deep familiarity with LLMs, prompt engineering, agents, tool use, and AI orchestration frameworks (LangChain, LlamaIndex, CrewAI, etc.) - Solid Development Foundation: Proficiency in Python and/or JavaScript. Comfortable building APIs, working with databases, and deploying to cloud environments as well as front end experience. Node JS, React. - Integration Experience: Track record connecting disparate systems via APIs, webhooks, or middleware. Experience with Airtable, Zapier, Make, or similar platforms is a plus - Platform Sensibility: Understands how internal tools and operational platforms are built and scaled. Can contribute to product thinking, not just feature execution - Cross-Functional Communicator: Can translate AI concepts for non-technical stakeholders and gather real requirements from business teams Requirements - The Employee’s performance will be measured and evaluated on meeting project deadlines, goals and objectives, quality and adoption of AI solutions delivered, cross-functional collaboration, 1% for the Planet participation, communication, and feedback. Benefits - This position requires passion for the space and a personal philosophy, “do whatever it takes to get the job done.”

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.