Principal Generative AI Developer and Lead, SVP

For additional information, please review .* 10+ years of relevant experience* **Leadership & Management:** Proven experience in a technical leadership or team management role, with a strong ability to mentor engineers, manage project priorities, and drive team performance.* **Architectural Expertise:** Demonstrated ability to design and architect scalable, high-availability, end-to-end AI and machine learning systems.* **Business Acumen:** Significant experience collaborating with non-technical business stakeholders to identify opportunities, define requirements, and articulate a clear AI strategy.* **AI Governance:** Strong understanding and practical experience in implementing governance, risk, and ethical guidelines for enterprise-grade AI solutions.* **Expert Python Proficiency:** Expert-level programming skills in Python and its core AI/ML ecosystem (e.g., NumPy, Pandas, Scikit-learn).* **Deep AI/ML Expertise:** Extensive, hands-on implementation experience with Machine Learning, Deep Learning, Generative AI, and Agentic AI systems.* **Advanced Data Expertise:** Proven expertise in designing and managing complex data handling, preprocessing, and validation pipelines for mission-critical AI applications.* **Advanced MLOps:** Deep, practical experience in MLOps, including containerization (Docker), orchestration (OpenShift/Kubernetes), CI/CD, and production deployment of AI models.* **LLMs:** Gemini, OpenAI models (GPT series), Copilot, Claude, Llama, and experience with Local Models.* **Frameworks:** LangChain, LlamaIndex, and the Hugging Face ecosystem (Transformers, Datasets, Tokenizers).* **Orchestration:** LangGraph and designing and building complex Multi-Agent Systems.* **Development:** Building production-grade, scalable services using Python, FastAPI, and asynchronous programming patterns.* **RAG (Retrieval-Augmented Generation):** Designing and implementing advanced retrieval techniques using Vector DBs (e.g., Pinecone, Chroma) and PostgreSQL (with pgvector).* **ML/DL Platforms:** PyTorch and/or TensorFlow for building and fine-tuning models at scale.* **Deployment & Monitoring:** Containerization with Docker, deploying resilient production APIs, and implementing comprehensive monitoring, logging, and alerting strategies.* **Applied AI Skills:** Mastery of Advanced Prompt Engineering, AI Workflow Design, and GenAI application optimization for cost, latency, and performance. #J-18808-Ljbffr