1,000+ matching jobs for “DevOps Cloud Engineer”How results work Exact titles rank first, then title variations and keywords in descriptions. These labels aren't qualification scores. Without keywords, recently added jobs appear first.
+4 locations
… Overview As part of Product & Engineering team within the Global Digital Network, the Senior Manager, AI Engineer will help advance Coca-Cola’s transformation into a digital-first, data-driven enterprise. We are seeking …
Added Oct 27, 2026
Principal Engineer Target Marketplace Technology About us Working at Target means helping all families discover the joy of …
Added Oct 16, 2026
… focus on reliability, observability, scalability, and responsible engineering. Role Overview As a Senior Engineer - AI Platform , you will be a senior individual contributor responsible for designing and building …
Added Oct 16, 2026
The Role and Impact: As a GPU Software Development Engineer , you will focus on enabling and optimizing Intel's GPUs by developing, backporting, and validating software …
Added Oct 27, 2026
Engineer Lead Sr. Enterprise Tech and Platforms Schedule: 8AM-5PM EST Hybrid 1: This role requires associates to be …
Added Oct 27, 2026
Position Overview The primary responsibility of the Principal DevSecOps and Release Engineer is to architect and implement comprehensive DevSecOps practices to support our casino systems. This role …
Added Nov 3, 2026
… Metropolis Synthetic Data Generation (SDG) team wants a highly motivated and experienced Senior Software Engineer to join us. At a company celebrated for its innovative visual computing efforts, you will contribute to …
Added Oct 30, 2026
… Technology (SCPT) organization supporting Demand Planning and Pricing (DPP) platforms . As a Lead Software Engineer , you will report to an Sr. Engineering Manager and collaborate closely with Demand and Assortment Planners, …
Added Oct 28, 2026
… measures to avoid recurrence. Collaboration: Work closely with engineering, product management, and DevOps teams to share insights, identify recurring issues, and drive improvements to the Databricks Data …
Added Nov 11, 2026
… measures to avoid recurrence. Collaboration: Work closely with engineering, product management, and DevOps teams to share insights, identify recurring issues, and drive improvements to the Databricks Data …
Added Oct 8, 2026
… measures to avoid recurrence. Collaboration: Work closely with engineering, product management, and DevOps teams to share insights, identify recurring issues, and drive improvements to the Databricks Data …
Added Oct 8, 2026
Pay posted by employer $86,800–$198,000
Security and Operations Engineer The Opportunity: We are looking for a SecOps Engineer who specializes in installing systems on cloud …
Added Oct 27, 2026
+1 location
Pay posted by employer $141,000–$184,000 per year
… software, and applications, as well as coach and mentor team members. The Lead Platform Automation Engineer role will offer you the flexibility to make each day your own, while working alongside people who care so …
Added Oct 15, 2026
… expertise with technical leadership to understand business processes, identify bottlenecks, and optimize cloud -compute performance. You will lead complex implementations across scalable, modular, and distributed …
Added Oct 27, 2026
… Experience with microservices architecture and distributed systems. Familiarity with CI/CD pipelines and DevOps practices. Exposure to cloud platforms (AWS, Azure, or GCP). Strong full-stack development skills, with …
Added Oct 18, 2026
+6 locations
Pay posted by employer $98,175–$115,500
… to the customer experience. The candidate will be adept with the agile software development lifecycle and DevOps principles. Essential Responsibilities: Design, develop, and support scalable software solutions that …
Added Nov 3, 2026
Pay posted by employer $80,000–$150,000 per year
We are seeking a Lead Data Engineer to support the design, implementation, maintenance, and lifecycle of enterprise data products starting with …
Added Nov 5, 2026
Pay posted by employer $120,000–$145,000
… Degree. 7+ years' development experience with Java technologies: latest Java, Spring Boot, Spring cloud , Spring security, ORM, JDBC. Good knowledge on the other programming languages: Go, NodeJS, Python. …
Added Oct 27, 2026
The Specialist IS Engineer will assist in designing, developing, and maintaining applications and associated data engineering …
Added Oct 15, 2026
+1 location
We are seeking a talented and driven Senior Software Verification Engineer to join our innovative team and tackle SW verification challenges in the domains of high-speed networking, …
Added Oct 27, 2026
Requirements · employer excerpt Education: 4-year degree in Computer Science, Engineering, or equivalent practical experience. Experience: 4–7 years of software engineering experience, with meaningful experience as a senior individual contributor. AI Experience: Hands-on experience building and shipping LLM-powered or agentic applications into production. LLM / GenAI: Strong experience with LLM integration, prompt engineering, structured outputs, and production AI application patterns. RAG: Practical experience building RAG systems, including retrieval, embeddings, metadata filtering, reranking, grounding, and evaluation. 6 more in the full description below.
About this opportunity Original employer description About Us About Team Role Overview Senior Engineer - AI Platform , you will be a senior individual contributor responsible for designing and building production-grade AI capabilities and helping shape the technical direction of the platform.LLM applications, RAG, AI agents, MCP, Java/Kotlin and distributed systems , translating emerging AI capabilities into reliable software that can operate at scale.real production experience building and shipping AI applications , not just experimenting with LLMs or proof-of-concepts.AI Engineering & Agentic Systems
LLM Applications: Build and integrate production-grade applications using large language models, including prompt engineering, model integration, structured outputs, and inference workflows.RAG: Design and implement Retrieval-Augmented Generation solutions covering retrieval, embeddings, metadata filtering, reranking, grounding, citations, and evaluation.AI Agents: Build agentic workflows using agent frameworks and tool-enabled architectures, including Model Context Protocol (MCP) and multi-step agent interactions.Agent Architecture: Design reliable patterns for agent, tool, and service interactions with clear separation of responsibilities and measurable execution behavior.Evaluation & Quality: Build approaches to evaluate AI systems for correctness, reliability, grounding, tool usage, and regression across model and prompt changes.Software Engineering & Architecture
System Design: Design scalable, resilient distributed systems that support AI workloads and high-volume production use cases.Java / Kotlin Engineering: Build backend services using Java or Kotlin, Spring Boot, microservices, APIs, and cloud-native patterns.Architecture: Drive design decisions for core platform components, balancing performance, scalability, maintainability, and operational requirements.Code Quality & Mentorship: Raise engineering standards through thoughtful code reviews, design reviews, mentoring, and strong implementation practices.Technical Problem Solving: Investigate and resolve complex issues across distributed services, AI workflows, performance, latency, and production reliability.Platform Reliability & Observability
Production Reliability: Build AI systems that are resilient, fault-tolerant, and suitable for production workloads.Observability: Design monitoring, logging, tracing, metrics, and operational signals that make AI applications measurable and diagnosable.Performance: Identify and improve latency, throughput, resource utilization, and model/tool execution efficiency.Operational Excellence: Participate in production readiness, incident analysis, reliability improvements, and engineering practices that reduce operational toil.Requirements
Education: 4-year degree in Computer Science, Engineering, or equivalent practical experience.Experience: 4–7 years of software engineering experience, with meaningful experience as a senior individual contributor.AI Experience: Hands-on experience building and shipping LLM-powered or agentic applications into production .LLM / GenAI: Strong experience with LLM integration, prompt engineering, structured outputs, and production AI application patterns.RAG: Practical experience building RAG systems, including retrieval, embeddings, metadata filtering, reranking, grounding, and evaluation.Agentic AI: Experience with AI agent frameworks, tool calling, agent orchestration, MCP, or similar agentic architectures.Backend Engineering: Strong proficiency in Java/Kotlin and Spring Boot , with experience building APIs and distributed services.Distributed Systems: Strong understanding of microservices, asynchronous systems, APIs, resilience, scalability, and failure handling.Reliability & Observability: Hands-on experience building production systems with monitoring, logging, metrics, alerting, and operational readiness.Cloud & DevOps: Experience with cloud-native environments and technologies such as Kubernetes, Docker, CI/CD, and managed cloud services.Engineering Practices: Strong coding, debugging, design, testing, code review, and problem-solving skills.Desired Qualifications
Experience building multi-agent systems or agent-to-agent architectures. Experience with Model Context Protocol (MCP) or similar tool/context integration patterns. Experience with vector databases, embedding systems, reranking, or modern retrieval infrastructure. Experience designing AI evaluation frameworks , including deterministic evaluation, LLM-based evaluation, and production regression testing. Experience with observability platforms and distributed tracing for AI or microservice workloads. Experience working with Kafka, Redis, or other distributed infrastructure technologies . Experience building internal platforms or reusable AI capabilities consumed by multiple engineering teams. Strong understanding of AI system reliability, security, governance, and responsible engineering practices. What Success Looks Like
Own and deliver major AI platform components. Make architectural decisions and defend them with data and engineering judgment. Build AI capabilities that are reliable, observable, and reusable. Establish strong engineering practices for agentic and LLM-based systems. Mentor engineers and raise the technical bar across the team. Help shape the platform's next generation of AI and agentic capabilities.
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