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Senior AI engineer builds and optimizes agentic AI systems that analyze legacy software codebases for federal healthcare modernization, using LLMs, RAG, and autonomous agents to deliver explainable, traceable answers.
Lead the design and implementation of AI platforms and strategies, focusing on Generative AI, LLMs, RAG, and AI agents for enterprise solutions in a remote role.
Designs, maintains, and optimizes Google’s global infrastructure network to ensure reliability, scalability, and performance for users and services, focusing on routing, automation, and cross-team collaboration.
As a Data Center Technical Operations Manager, you will be involved in every aspect of colocation operations of our electrical, cooling, and IT infrastructure. You will partner with the Google data center engineering…
About Jakala We are Jakala — a data, AI and experience agency. Our team builds production-grade web applications and applied AI systems for enterprise clients in the healthcare and life sciences space. The work spans…
Build and optimize agent efficiency systems—cost/latency telemetry, smart model routing, deferred execution—for Google Cloud's Agent Development Kit and Vertex AI serving stack, working with LLMs at scale.
Builds and optimizes Borglet, Google’s node agent for managing user processes, focusing on scalable, secure infrastructure for AI/ML workloads and hyperscale computing.
Lead/Principal Full Stack Developer building AI-powered React applications with TypeScript/Node.js backends, integrating LLMs and agentic systems on AWS/GCP.
Anor Bank приглашает Senior AI Engineer Мы ищем опытного Senior AI Engineer , который будет разрабатывать и внедрять современные AI-решения для автоматизации бизнес-процессов и создания интеллектуальных продуктов.…
Overview With more than 45,000 employees and partners worldwide, the Customer Experience and Success (CE&S) organization is on a mission to empower customers to accelerate business value through differentiated…
Build and deploy production-grade data pipelines and LLM-based solutions for clients, using Python, SQL, dbt, Spark, Airflow, and frameworks like LangChain or LlamaIndex.
Leads a team of software engineers developing embedded software, diagnostics, and tools for custom SoCs, servers, and SmartNICs to optimize system health, test performance, and solve reliability issues across Google’s global data centers.
Lead cross-functional technical programs to scale AI developer systems and infrastructure at Google, managing project lifecycles and driving architectural alignment. Core technologies include AI/ML platforms, distributed systems, and data analysis tools.
Google isn't just a software company. The Hardware Operations team is responsible for monitoring the state-of-the-art physical infrastructure behind Google's powerful search technology. As an Operations…
Embedded engineer at Google Cloud who codes, ships, and hardens production-grade agentic AI workflows (Gemini Code Assist, multi-agent systems) directly within customer environments using Google Cloud's Vertex AI stack and protocols like MCP/A2A.
Like Google's own ambitions, the work of a Software Engineer goes beyond just Search. Software Engineering Managers have not only the technical expertise to take on and provide technical leadership to major…
Bridges big data environments and media strategy at an ad agency by managing SQL data transformations, building client dashboards (Looker Studio, Tableau, Power BI), overseeing tag/pixel implementation (GTM, Adobe Launch), and supporting MMM and AI projects.
Data Engineer building and maintaining scalable data pipelines, warehouses, and data services on GCP (BigQuery, Airflow, Dataform/DBT, Pub/Sub, Cloud Functions) for a multi-carrier shipping SaaS platform, with an AI-augmented insights focus.
The Principal AI Software Developer leads the design and implementation of large-scale, mission-critical AI and LLM systems for federal agencies using a modern cloud stack including Next.js, Terraform, and major cloud providers. This hands-on role involves architecting AI solutions, establishing MLOps practices, and ensuring compliance with federal security and AI policy standards.
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