Senior AI Engineer (f/m/d)

Senior AI Engineer (f/m/d) asap 6 months Freelance Berlin Deutsch 4120 For an international customer we are looking for a Senior AI Engineer (f/m/d). Your tasks will be: Design, build, evaluate and maintain AI-driven software systems that solve real engineering and documentation challenges—ensuring reliability, maintainability, and long-term value at scale. Your work is deeply software engineering–driven, with AI as a powerful enabler. Turn User Problems into Productive AI Solutions  Bridge the Gap: Engage with internal stakeholders across engineering, tendering, and operations to deeply understand user needs, document workflows, and identify pain points.  Design for Value: Translate complex user requirements into AI-enabled concepts and service designs that deliver measurable business value, moving beyond prototypes to real-world impact.    Data Science, Evaluation & Mentorship  Lead AI Evaluation & Prompt Engineering: Treat prompt engineering as a scientific discipline; design and execute rigorous evaluation strategies to measure output quality, retrieval accuracy, and system behavior.  Drive Data-Centric Development: Oversee data quality standards and dataset curation to ensure our models are grounded in accurate, high-value context.  Mentor & Guide: Lead working students and junior talent through data science explorations, guiding them in dataset creation, experimental evaluation, and the iterative improvement of AI capabilities.    AI Engineering  Build Production AI Services: Develop and maintain high-quality AI solutions, focusing on model integration, semantic indexing, and advanced retrieval architectures (LLMs, RAG, hybrid retrieval, and vector search).  Drive End-to-End Delivery: Own features fully—from requirements and design to implementation, testing, deployment, and monitoring—while ensuring robust CI/CD practices and high coding standards.  Engineer Scalable Systems: Develop resilient backend APIs, agentic AI workflows, and data pipelines that ensure reliability and observability, strictly adhering to modern engineering standards Following know-how is required: 5+ years of experience in software engineering, with a strong focus on AI, NLP, or Information Retrieval.  Generative AI Stack: Deep knowledge of NLP, LLMs, and Prompt Engineering as a structured discipline.  Production Mindset: A proven track record of delivering production-grade software, not just prototypes or notebooks. You have experience operating AI-backed services in enterprise settings.  Process Mastery (SDLC & CRISP-DM): You bridge the gap between experimental Data Science (CRISP-DM) and rigorous Software Engineering (SDLC). You know how to structure iterative AI experiments into deterministic, reliable release cycles.  Advanced Python Proficiency: You write clean, composed, and typed Python (3.11+) code. You utilize modern features (async/await, Pydantic) and manage dependencies/packages effectively.  Software Craftsmanship & Quality: You treat AI code as production software. This means writing comprehensive tests (pytest, mocking), enforcing code quality via pre-commit hooks (ruff, mypy), and adhering to strict Git workflows (merge requests, code reviews).  Development Autonomy: You take ownership of your local development environment and tooling. You are comfortable setting up Docker containers and managing your own configuration.  Retrieval Architectures: Hands-on experience with RAG, hybrid retrieval strategies, GraphRAG, and vector search technologies (e.g., OpenSearch).  Evaluation: Experience designing automated evaluation pipelines to benchmark AI output quality and retrieval performance.  Nice to Have: experience with cloud-based AI platforms (AWS Bedrock, Azure OpenAI), knowledge of Model Context Protocol (MCP) and modern API interface standards.