AI Engineer

För Partners räkning söker vi en AI Engineer Enligt nedan. As a Senior AI Engineer, you’ll lead the development of AI-driven products from concept to delivery. You'll design, build, and iterate on applications that directly support business needs, embedding AI into the daily workflows. This is a hands-on engineering role with product ownership, you’ll work closely with users and cross-functional colleagues to define requirements, test ideas, and scale what works. While the role includes platform responsibilities, the emphasis is on building usable, end-to-end AI products that solve real problems and deliver value. Key responsibilities include: • Design and build reliable, scalable, and high-performing AI solutions and infrastructure. • Develop AI workflows using LLM APIs, Retrieval-Augmented Generation (RAG), and agent frameworks. • Collaborate across teams to define and ship new AI features and enhancements. • Manage applications and infrastructure on Google Cloud Platform (GCP). • Work with Docker, Kubernetes, CI/CD pipelines, and observability tools. • Ensure ethical, secure, and compliant use of AI across all solutions. • Stay current with developments in AI, LLMOps, and platform engineering. About you You’re a curious and committed engineer who thrives in collaborative, fast-paced environments. You care about impact and quality, and enjoy building systems that scale and last. Essential skills and experience: • Proven experience in AI, machine learning, and software engineering (minimum 3 years). • Strong Python skills and a solid grasp of data structures, algorithms, and design patterns. • Familiarity with LLM integration, RAG, LangChain, or similar technologies. • Hands-on experience with cloud platforms (preferably GCP), containerization (Docker, Kubernetes), and CI/CD. • Knowledge of backend and API frameworks (e.g. FastAPI, REST, GraphQL). • Experience with version control (e.g. Git) and Agile methodologies. • Understanding of database technologies such as BigQuery, PostgreSQL, Redis, or Elasticsearch. • Awareness of, security, and ethical considerations in AI. • Strong communication skills - ability to explain complex concepts for targeted audiences Nice to have: • Platform Engineering or Site Reliability Engineering (SRE) experience. • Background in NLP, especially for summarization and information extraction. • Exposure to machine learning libraries like TensorFlow, PyTorch, or scikit-learn. • Experience with agentic workflows and MCP. • Experience with data transformation tools like dbt.