Top Tech Jobs & Startup Jobs

Deploys, integrates, and scales enterprise generative AI solutions in customer cloud environments. Responsibilities include architecting GCP and Vertex AI infrastructure, deploying and optimizing LLMs, building RAG data and vector search pipelines, managing GPU/TPU workloads on GKE, automating infrastructure with Terraform, and advising clients on AI safety, prompt engineering, hallucinations, and inference costs. The role also collaborates with research and platform teams and requires travel to client sites.

The Databricks Architect will design and implement large-scale data solutions, optimizing performance and reliability, while leading initiatives in data engineering.

The Machine Learning Engineer will develop software solutions, optimize data pipelines, and deploy machine learning models using cloud platforms and best practices.

The Technology Partner leads client engagements in Data & Insights, providing technology leadership, thought leadership, and mentoring while driving transformation agendas and solutions development.

The Azure Architect will design and migrate enterprise technology products to Azure, guiding development teams through all stages while ensuring compliance and security.

Lead end-to-end data science initiatives, build ML models, collaborate with cross-functional teams, and communicate insights to business leaders.

Lead the design of data architectures in Multi-Cloud environments, oversee migration of legacy systems, develop predictive models, and mentor technical teams.

Looking for a Data Engineer experienced in Dataiku to design and maintain data pipelines and infrastructure, ensuring data flow and integration across teams.

Lead design and delivery of enterprise-scale AI platforms and production-grade Generative/Agentic AI solutions. Define AI architecture, standards, and roadmaps; ensure security, governance, and performance; evaluate emerging technologies; mentor teams and partner with engineering, data, security, and business stakeholders to accelerate enterprise AI adoption.

The Google Workspace Administrator will manage and integrate Google Workspace environments, support M&A efforts, and collaborate on security and identity management processes, while automating tasks through scripting.