Senior GenAI Engineer

Our mission is to transform how people and machines work together to push the boundaries of human productivity. A leader in Industrial AI, Augury helps the world’s manufacturers leverage real-time production insights to drive new levels of efficiency. Combining predictive and prescriptive AI technology with industry expertise, production teams can proactively address alerts, minimize downtime, reduce asset costs, and maximize yield and capacity. Our customers achieve payback in six months or less, enabling global scale. We're looking for team members excited to partner with the world's manufacturers and build the future of production together. As a Senior GenAI Engineer, you will work closely with our central Algorithm, Product, and Engineering teams to design, build, and deploy scalable GenAI and AgenticAI solutions for industrial environments. This role sits at the intersection of machine learning, large language models, time-series analytics, and distributed systems. You will own the full lifecycle of GenAI applications, from experimentation and prototyping through production deployment, observability, and optimization, helping transform Augury’s AgenticAI vision into intuitive, high-impact workflows that deliver measurable customer value and ROI. This is an opportunity to solve complex, real-world AI challenges using massive multi-modal industrial datasets while deploying production-grade AI systems used by global manufacturers. A Day In Your Life Own the end-to-end lifecycle of GenAI and AgenticAI solutions, from problem definition and experimentation through deployment and monitoring. Design and implement scalable AI systems leveraging: Time-series modeling Signal processing LLMs and embeddings Agent orchestration frameworks Classical ML and deep learning approaches Build and optimize production-grade LLM pipelines, including RAG systems, embedding pipelines, multi-agent workflows, tool orchestration, and evaluation frameworks. Architect AgenticAI applications utilizing diverse inputs such as sensor-based industrial time-series data, unstructured text, and existing ML systems. Develop backend services and APIs in Python to support AI agents, orchestration workflows, and integrations with streaming/data infrastructure (e.g., Kafka, NSQ). Partner closely with Product, Engineering, Data Science, and customer stakeholders to identify opportunities and deliver impactful AI-powered solutions. Contribute to scalable MLOps and LLMOps frameworks for deployment, observability, evaluation, and monitoring. Monitor and improve production systems for performance, hallucinations, model drift, reliability, and cost optimization. Translate research and experimentation into scalable, maintainable, production-ready systems. Drive engineering excellence through architecture discussions, code reviews, and technical leadership. What You Bring 4+ years of experience spanning Data Science, Machine Learning, and/or Generative AI. Hands-on experience building and deploying GenAI or AgenticAI applications in production environments. Strong experience with: LLMs and prompting techniques Embeddings and vector databases RAG architectures Agent orchestration frameworks Evaluation methodologies (HITL, LLM-as-a-Judge, deterministic evals) Experience with modern AI/ML frameworks such as PyTorch, TensorFlow, Hugging Face, LangChain, CrewAI, AutoGen, and LangSmith. Strong Python development skills across model development, backend services, deployment, and monitoring. Experience building scalable APIs, distributed systems, and microservices. Familiarity with streaming and data infrastructure platforms. Experience working in Agile environments with a bias toward rapid iteration, experimentation, and continuous improvement. Proven ability to collaborate across globally distributed Product, Infrastructure, Data Engineering, and R&D teams. Ability to balance research innovation with pragmatic engineering execution. Experience optimizing LLM/API usage and infra