Key skills
CloudDistributed SystemsKubernetesLinuxOpenStackPythonAILLMRAGAnalyticsRepositoryCI/CDRemote Work
About this role
Role Overview
- Build AI-assisted tooling for engineering workflows
- Improve developer productivity and operational efficiency
- Design systems that reduce repetitive manual engineering work
- Develop AI-driven solutions for pipeline analysis, failure classification, flaky test detection, release validation, dependency impact analysis, build optimization, deployment risk analysis
- Improve reliability and visibility of engineering pipelines
- Build AI systems for troubleshooting assistance, incident investigation, log analysis, engineering knowledge retrieval, operational recommendations
- Automate engineering support and operational workflows
- Design and implement engineering copilots, RAG systems, context management systems, internal engineering assistants, workflow automation agents
- Integrate AI with engineering systems, repositories, CI/CD platforms, documentation, observability tools, and operational data sources
- Deploy and maintain production-grade AI services
- Ensure observability, monitoring, evaluation, and operational reliability
- Optimize AI systems for latency, cost, and scalability
- Maintain secure and maintainable integrations
Requirements
- Strong software engineering fundamentals
- Strong Python skills
- Experience building backend systems, APIs, and automation tooling
- Experience with distributed systems and Linux environments
- Practical experience with LLM systems and AI tooling
- Experience with: RAG architectures embeddings vector search workflow orchestration AI evaluation
- Ability to build production systems, not just prototypes
- Experience with CI/CD systems
- Familiarity with: Kubernetes containers observability tooling infrastructure automation cloud-native environments
- Understanding of operational workflows and engineering lifecycle challenges
- Nice-to-Have Experience with OpenStack ecosystems
- Experience with large-scale monorepo or multi-repository environments
- Experience with engineering analytics and developer productivity metrics
- Familiarity with infrastructure observability and incident management systems
Tech Stack
- Cloud
- Distributed Systems
- Kubernetes
- Linux
- OpenStack
- Python
Benefits
- Flexible hours and remote work options
- Competitive compensation with diffrent benefits depending on your location and type of contract
- Recognition programs
- Space for creativity and experimentation within the company’s goals
- Supportive, engineering-driven culture with minimal bureaucracy
- The chance to influence infrastructure decisions from day one
- A smart, friendly team that values reliability, simplicity, and automation