Design, deploy, and manage AWS cloud and hybrid infrastructure using Infrastructure as Code to support the OSS core network platform. The role involves maintaining CI/CD pipelines and managing the operational lifecycle of third-party vendor software.
Remote Software Development Jobs in Latvia (78)
Remote in = Latvia
Job category = Software Development
The role involves owning product validation and quality engineering for internal software, including defining test strategies and building automated regression suites. The engineer will manage test environments, drive defect resolution, and ensure software reliability before shipment.
Design, build, and deploy innovative telecom software components for a global cellular broadband network in space. The role involves translating architectural designs into production-ready code and maintaining integration tests and CI/CD pipelines.
Lead SEO strategy and KPI progress for clients by designing automated workflows and AI-supported systems. Act as the primary strategic contact for clients, managing expectations and connecting SEO performance to business growth.
Produce 15-20 high-performing AI-driven short-form ads per week for Meta. Lead and manage a team of editors, overseeing quality control, KPIs, and hiring/firing processes.
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Senior Product Manager, Infrastructure Observability | Ireland | Remote
Grafana Labs
·
Full Time
·
9 Weeks Ago
Grafana Labs
Define the vision and roadmap for Infrastructure Observability products, specifically Kubernetes Monitoring and Cloud Provider Observability. Collaborate with engineering and GTM teams to simplify the user experience and drive product adoption within Grafana Cloud.
The NoSQL Administrator will be responsible for the administration, maintenance, and architecture of Redis and Elasticsearch platforms. They will also implement DataOps practices and automate processes using various tools and technologies.
Design and build a governed enterprise AI platform including orchestration, model routing, and RAG layers. Manage the full stack from tool selection and deployment to security, governance, and enabling non-engineers to ship workflows.
Lead the end-to-end design and delivery of cloud-native, AI-ready data platforms for omnichannel retail clients. Balance pre-sales discovery and C-level stakeholder management with technical oversight of engineering pipelines and models.
Design and scale the company's operational platform by transforming manual processes into automated, AI-assisted systems. Collaborate with Product, Engineering, and Operations teams to map workflows and implement scalable internal logic.
Build and evolve Lambda-first microservices to handle real money flows and integrations for a fintech platform. Design and maintain type-safe REST APIs and event-driven workflows using AWS services.
You will build and evolve the agent harness by implementing hooks, permission gates, and context compaction to ensure reliable task completion. Additionally, you will architect planner/executor/evaluator pipelines and manage agent memory to support long-horizon, multi-session execution.
Design, develop, and support cloud and locally hosted solutions to facilitate efficient service deployment and operations. Collaborate with the research and development teams to automate processes, improve infrastructure, and resolve complex operational issues.
Design and build distributed systems that autonomously manage Kubernetes infrastructure at scale. Write production-grade Go services to interact with cloud provider APIs for real-time resource management.
Design, build, and operate backend services, Kubernetes operators, and controllers in Go across major cloud platforms. Solve complex infrastructure-layer problems including networking, scheduling, storage, and container runtime internals.
You will take ownership of Android development, choosing the right technologies and approaches to meet long-term product needs. You will also lead the development of complex features, conduct code reviews, and mentor team members to ensure high engineering standards.
The role involves conducting applied research in AI/ML to solve real-world problems in home design using various data types, and designing, implementing, and validating prototypes and MVP solutions for production features. This includes training and iterating on models, contributing to AI-driven features like computer vision systems, and collaborating with engineers to deploy research into production.
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The role involves engineering robust solutions using advanced Python and SQL to capture, process, and scale data pipelines by implementing and maintaining web scrapers. Key duties include improving the scraping platform for data quality and performance, taking ownership of architectural components, and reducing technical debt through code contributions and reviews.
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