Sr AI/ML Engineer

When you’re the best, we’re the best. We instill an environment where employees feel engaged, satisfied and able to contribute their unique skills and talents while living and working as their authentic selves. We provide extensive opportunities for personal and professional development, building both employee competence and organizational capability to fuel exceptional performance through an inclusive environment both now and in the future. Summary: In this role, you will design, build, and deploy scalable AI and machine learning solutions that drive business impact. You will lead the full AI lifecycle from experimentation through production, developing both traditional ML models and Large Language Model (LLM)-powered systems such as Retrieval-Augmented Generation (RAG) pipelines and agentic workflows. You will collaborate across teams to translate complex problems into reliable, high-performing solutions aligned with client needs. We are seeking engineers who are driven, curious, and energized by the pace of AI innovation, bringing emerging tools and techniques into practical, production-ready systems while taking ownership and helping shape the next generation of AI capabilities. Responsibilities: Lead the design, development, and deployment of machine learning models and LLM-based applications. Translate business challenges into scalable AI solutions and define success [... source excerpt omitted ...] ment strategies, CI/CD pipelines, and MLOps workflows. Implement monitoring, drift detection, retraining pipelines, and model lifecycle management practices. Design and maintain production-grade data pipelines ensuring validation, lineage, and reproducibility. Mentor team members, influence AI architecture decisions, and promote responsible AI governance. Stay current with advancements in AI/ML, including LLMs, agentic systems, tooling, and applied best practices, and integrate relevant innovations into team solutions. Qualifications: Relevant degree preferred. Advanced degree in Computer Science, Engineering, Data Science, or a related field is a plus. 5 or more years of re [... source excerpt omitted ...] ls into production environments required. Experience building and deploying LLM-powered applications such as RAG systems, Agentic workflows required. Strong Python expertise and production-grade software engineering practices required. Experience with model serving frameworks and API development (e.g., FastAPI, MLflow, etc.) required. Experience with vector databases and embedding workflows required. Familiarity with orchestration frameworks such as LangChain, LlamaIndex, or similar tools required. Experience with CI/CD pipelines, containerization, and cloud-based deployment environments required. Strong understanding of evaluation methodologies for both predictive ML and LL