Junior AI Engineer

📋 Description

• Create AI-assisted tools to enhance engineering workflows.

• Boost developer productivity and operational effectiveness.

• Design systems aimed at minimizing repetitive manual engineering tasks.

• Support large-scale software delivery across multiple components.

• Develop AI-driven solutions for pipeline assessment, failure classification, flaky test detection, release validation, dependency impact evaluation, build optimization, and deployment risk analysis.

• Enhance the reliability and visibility of engineering pipelines.

• Construct AI systems for troubleshooting support, incident investigation, log analysis, engineering knowledge retrieval, and operational recommendations.

• Automate engineering support and operational processes.

• Design and implement engineering copilots, RAG systems, context management systems, internal engineering assistants, and 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, assessment, and operational reliability.

• Optimize AI systems for latency, cost-effectiveness, and scalability.

• Maintain secure and manageable integrations.

⛳️ Requirements

• Strong foundation in software engineering principles.

• Proficient in Python programming.

• Experience in developing backend systems, APIs, and automation tools.

• Familiarity with distributed systems and Linux environments.

• Practical experience with LLM systems and AI tools.

• Knowledge of RAG architectures, embeddings, vector searches, workflow orchestration, and AI evaluation.

• Capability to create production systems rather than just prototypes.

• Experience with CI/CD systems.

• Understanding of Kubernetes, containers, observability tools, infrastructure automation, and cloud-native environments.

• Insight into operational workflows and challenges within the engineering lifecycle.

• Nice-to-Have: Familiarity with OpenStack ecosystems, large-scale monorepo or multi-repository setups, engineering analytics, developer productivity metrics, and infrastructure observability and incident management systems.

🏝️ Benefits

• Flexible working hours and options for remote work.

• Competitive salary with various benefits based on location and contract type.

• Recognition programs.

• Opportunities for creativity and experimentation aligned with company objectives.

• A supportive, engineering-focused culture with minimal bureaucracy.

• The opportunity to influence infrastructure decisions from the outset.

• A smart, friendly team that prioritizes reliability, simplicity, and automation.