Agentic AI Engineer - Remote Automation & Troubleshooting

AgileEngine; Warszawa; On-site; PLN 120,000 - 180,000; Full time

Benefits offered by this job

Growth without limits

Competitive compensation

Flexibility: 100% remote with flexible

Meaningful, modern projects

Collaborative culture

Well-being & support

Job summary

AgileEngine is seeking an Agentic AI Engineer to build AI agents that analyze infrastructure discovery logs and automate complex troubleshooting using Python and REST APIs. This software engineering role focuses on production-grade solutions rather than research.

You will integrate Gen AI capabilities such as Retrieval-Augmented Generation (RAG) and vector databases into production systems, designing scalable data pipelines and robust API integrations.

Qualifications

• 4+ years of experience in software engineering with strong Python development and REST API design skills.
• Experience integrating Gen AI APIs (e.g., OpenAI, Anthropic) into software apps and understanding RAG and vector databases.
• Solid SDLC toolchain experience including CI/CD, automated testing, code quality and release management.
• Upper-intermediate English level.

Responsibilities

• Design and build AI agents that continuously analyze Discovery logs, execution results, errors and failures at scale.
• Develop agents to classify and correlate failures, troubleshoot, identify root causes, and propose corrective actions.
• Enable agents to analyze and recommend corrections to probes and patterns with testing and guardrails before production.
• Create and manage data-processing pipelines and API integrations feeding telemetry into the AI ecosystem.

Skills

Python development

REST API design

Gen AI APIs

RAG concepts

SDLC practices

Tools

Git/GitHub

Jenkins

Job description

AgileEngine is seeking an Agentic AI Engineer to build AI agents that analyze infrastructure discovery logs and automate complex troubleshooting using Python and REST APIs. This software engineering role focuses on production-grade solutions rather than research.

You will integrate Gen AI capabilities such as Retrieval-Augmented Generation (RAG) and vector databases into production systems, designing scalable data pipelines and robust API integrations.