We are seeking a AI Lead to drive the development and deployment of intelligent applications powered by ambient IoT platform. This role will be at the forefront of building AI-native interfaces that connect the physical and digital worlds redefining how users interact with real-time data, business operations, and physical assets.
This is a flexible leadership position: Ideal for someone who can build and lead a team, or an exceptional technical expert capable of executing as a high-impact individual contributor. The role reports to the Director of Strategy and will be central to shaping AI roadmap across internal tools, customer-facing solutions, and SDKs for external developers.
Responsibilities
AI Product Execution: Lead the development of GenAI-driven products, such as intelligent agents, copilots, and self-serve interfaces for real-world sensing and IoT data.
Architecture & Engineering: Design scalable, secure, and maintainable architectures for deploying LLM-powered services in production.
AI/ML Ops & Infrastructure: Own the full lifecycle of AI solutions prompt engineering, model evaluation, vector search, function calling, monitoring, retraining.
Team Leadership (optional): Mentor and grow a team of AI engineers and applied researchers, or collaborate across squads as a senior IC.
Cross-functional Collaboration: Work with data scientists, software engineers, product managers and business stakeholders to embed generative AI into the core of data product strategy.
Customer Use Cases: Translate ambient IoT data into actionable AI experiences supporting applications in logistics, sustainability, inventory management, and supply chain visibility.
Developer Platforms: Help build the SDKs and APIs that let customers and partners create their own AI-powered workflows using technology.
Experimentation & Research: Stay at the frontier of GenAI advancements (LLMs, RAG, agents, vision-language models) and apply them to real-world constraints and data environments.
Requirements: Proven experience developing and deploying generative AI solutions (chatbots, agents, copilots, RAG systems) in production.
Strong software engineering background proficiency in Python, experience with LLM frameworks (e.g., LangChain, LlamaIndex, Haystack), and deployment tools (e.g., FastAPI, Docker, Kubernetes).
Deep familiarity with LLMs (OpenAI, Claude, Mistral, etc.) and embedding models, including retrieval and vector database design (e.g., Weaviate, Pinecone, FAISS).
Experience integrating LLMs with real-time or IoT data, or streaming data sources.
Working knowledge of MLOps and production-grade AI systems versioning, monitoring, observability, security.
Excellent communication skills comfortable interfacing with engineers, data teams, and non-technical stakeholders.
Experience in fast-paced, startup-like environments self-directed, curious, and execution-driven.
This position is open to all candidates.