• Collaborate with cross-functional teams to design, develop, and deploy scalable software products that incorporate machine learning and AI models. • Build reusable Python packages to support the implementation of ML/AI algorithms and data-processing pipelines. • Contribute to the design of AI systems, including components for retrieval-augmented generation (RAG), LLM integration, and agent-based workflows. • Develop agentic evaluation and monitoring frameworks to assess model reasoning, consistency, and fairness. • Evaluate database design and create optimized performance queries for efficient data processing and retrieval. • Break down complex MLE and AI tasks into manageable user and technical stories, ensuring efficient and effective implementation. • Ensure high-quality test coverage of ML code and participate in peer reviews to provide valuable recommendations. • Stay updated on the latest advances in machine learning engineering, generative AI, and AI system orchestration, and incorporate relevant practices into our workflows. • Contribute to continuous delivery and Agile development processes, adhering to best practices in ML and AI engineering.