Top Tech Jobs & Startup Jobs in Denver & Boulder, CO

Lead architecture and hands-on implementation of large-scale Generative AI and agentic systems. Build production-ready RAG, embedding fine-tuning, vector search, and MLOps pipelines on Google Cloud. Advise clients in pre-sales, mentor engineers, and ensure reliability, latency, cost, and responsible-AI controls for high-stakes deployments.

Design, optimize, and operate production LLM inference and training pipelines. Improve latency, throughput, and GPU utilization using techniques like batching, quantization, FlashAttention, and kernel-level profiling. Deploy and autoscale multiple models on shared GKE GPU clusters, consult with clients on performance and cost requirements, and carry prototypes to robust, scalable production services.

Lead hands-on cloud implementation and technical ownership for Google Cloud environments: design, deploy, and operate secure, scalable infrastructure; implement hybrid connectivity, security guardrails, observability, and automation; lead delivery and mentor engineering teams.

Lead client-facing organizational change for AI and Workspace transformations: design change strategies, engage executives, build training and champion networks, run Gemini pilots, measure adoption, and sustain new behaviors across enterprises.

Lead cloud architecture initiatives, driving multi-cloud adoption and governance, optimizing costs, implementing security measures, and mentoring engineers.

The Client Partner will drive sales, maintain client relationships, oversee service projects, support marketing efforts, and manage account strategy within the East region.

Lead enterprise cloud strategy and architecture on Google Cloud, drive multi-cloud interoperability, enforce governance and security, optimize cost, deliver large-scale implementations (GKE, BigQuery, Vertex AI), mentor senior engineers, and promote GitOps and automation across the delivery lifecycle.

As a Senior AI Engineer, you will develop and optimize Generative AI applications, manage AI pipelines, collaborate with clients, and ensure production delivery with MLOps best practices.

Lead architecture and implementation of cloud-native data platforms on Google Cloud (BigQuery). Build unified batch/streaming pipelines, enforce IaC with Terraform, implement open table formats and governance (Dataplex/Data Catalog), automate data quality/lineage, partner with analytics and product teams, and mentor data engineers.