Be the Architect Builder: Act as the technical engine for AI products. You are responsible for designing, developing, and implementing end-to-end AI products that solve high-impact industrial challenges.
Revolutionize the Build: You don't just follow standard ML workflows; you innovate on how to build them faster. You will champion the use of Agentic Coding Frameworks and LLMOps to accelerate our time-to-market and automate the development lifecycle.
Iterate at Speed: Lead the technical execution of the product lifecycle using a lean, MVP-driven approach. You focus on rapid prototyping, turning user feedback into code, and ensuring continuous deployment of production-grade models.
Bridge Code Value: You speak "Deep Learning" and "Business Value" fluently. You will translate complex AI/Cloud architectures into scalable technical solutions, ensuring our technical debt stays low while our value delivery stays high.
Technical Leadership Mentorship: In a large organization, technical clarity is key. You will proactively clear technical roadblocks, mentor junior engineers, and align stakeholders on the feasibility and scalability of AI solutions.
Startup/Fast-Growth DNA: You have a proven track record (ideally 5+ years) in a startup or high-growth tech environment. You are used to rapid pivots and taking full ownership of your code and its impact.
The "Pusher" Personality: You don't wait for a Jira ticket. You identify technical gaps and rally the team to solve them. You are comfortable with ambiguity and thrive when things move fast.
Project Ownership: Demonstrated ability to lead projects from conception to endpoint serving in real-world production environments.
AI Agentic Mastery: Deep practical knowledge of AI/ML (LLMs, RAG). Crucially, you have experience with Agentic Frameworks (e.g., LangChain, CrewAI, Autogen) and AI-native development tools (e.g., Claude Code, Codex, or Cursor).
Engineering Roots: Strong proficiency in Python and modern ML frameworks (e.g., PyTorch, TensorFlow). You understand how to build "production-grade" software and scalable cloud architectures (AWS or Azure).
MLOps Infrastructure: Experience with MLOps/LLMOps pipelines, version control (GitLab/GitHub), and big data technologies (e.g., Snowflake, Spark). You build for scalability, not just for a notebook.
Radical Clarity: You communicate directly and concisely. You can explain a gradient descent issue to a developer and then immediately pivot to explaining the ROI of an AI agent to a stakeholder.
Resilience: You are comfortable with constructive debate and have the "grit" to push back when necessary to protect the technical integrity and speed of delivery.
Language: Fluent English is a must; German is a "nice to have." Education: Advanced degree in Computer Science, Data Science, Machine Learning, Mathematics, Statistics, Physics, or a related field.