Experience avec les modeles multimodaux, l'apprentissage par renforcement, la generation augmentee par la recherche et les principes d'IA responsable. Bachelor's or Master's in CS, Engineering, or related field (PhD welcome but not required). 10 + years of professional software development, including 5 + years building production AI/ML or GenAI systems at scale. Deep expertise in Python and frameworks like TensorFlow, PyTorch, plus LangChain, LangGraph, and foundation-model orchestration. Proven ability to build on foundation-model APIs and use AI daily in your workflow (GitHub Copilot, Windsurf/Cursor, Claude Code, etc.). Hands-on mastery of cloud platforms (GCP, AWS or Azure), containerization (Docker, Kubernetes), and modern CI/CD and IaC practices. Strong background in distributed systems, micro-services, and data platforms (SQL, NoSQL, vector stores). Experience with multi-modal models, reinforcement learning, retrieval-augmented generation, and responsible-AI principles. Advanced knowledge of GCP services--Vertex AI, BigQuery, GKE, DataFlow, Kubeflow--and streaming frameworks (Kafka, Pub/Sub). Track record of thought leadership: papers, open-source contributions, or conference talks. Comfortable guiding teams in agile and DevOps environments, balancing speed with reliability. A thought leader who reads research papers for fun and turns them into production-ready platforms. Energized by ambiguity, end-to-end ownership, and setting the pace in an AI-first culture. Inclusive, candid, and relentlessly customer-obsessed, with a knack for inspiring both technical and non-technical stakeholders. Please add a link in your resume (GitHub repo, blog post, Kaggle entry, etc.) that shows something you taught yourself in the last six months and why it excited you. Set the technical vision for GenAI systems--own the roadmap, architecture, and standards for reliability, security, and performance. Architect and build cloud micro-services in Python with LangChain, LangGraph, ADK, MCP, A2A and web-first frameworks such as FastAPI, Streamlit, Gradio, FastHTML--scaling multimodal (text + image + video) models to millions of users. Drive innovation--experiment with transformers, diffusion, and multi-modal architectures; integrate emerging research into production workflows. Lead end-to-end delivery--from ideation and data strategy to model fine-tuning, deployment, and continuous optimization, meeting strict latency and compliance targets. Mentor and multiply talent--coach engineers, run design reviews, and raise the technical bar through candid feedback and knowledge-sharing sessions. Champion operational excellence--define SLOs, instrument deep telemetry, lead incident response, and run blameless post-mortems in a true DevOps model. Influence across UKG--partner with product, UX, data science, security, and leadership to align technical decisions with business outcomes and inspire a culture of relentless learning
