AI/ML Engineer

TL;DR

AI/ML Engineer (AIOps): designing and developing AI agents for operations including Incident Triage, Dependency Analysis, Runbook Interpreter, Change Risk with an accent on ML models for alert correlation, anomaly detection, and root-cause prediction. Focus on implementing Agent Maturity Gate framework, building confidence scoring systems, and deploying agents using hirify.global ACE platform.

Location: Work from the European Union region and a work permit are required

Company

Global AI-first digital transformation and engineering partner with over 5,000 professionals across 16 countries, specializing in AI, Data, Cloud, and delivering solutions for clients like McLaren, Spotify, ING in CEE region.

What you will do

• Design and develop AI agents for operations: Incident Triage, Dependency Analysis, Runbook Interpreter, Change Risk.
• Build and deploy AI KT Agent ingesting codebase snapshots, IaC, and incident history.
• Implement Agent Maturity Gate framework: OBSERVE, RECOMMEND, CONTROLLED EXECUTE, LIMITED AUTONOMY.
• Develop ML models for alert correlation, anomaly detection, root-cause prediction trained on client data.
• Build confidence scoring systems and maintain audit trails for agent decisions.
• Deploy agents across regional instances and integrate into SRE workflows.
• Measure and report agent effectiveness: accuracy, false positives, human overrides.

Requirements

• Work from the European Union region and a work permit are required
• 3-6 years in ML engineering, AIOps, or applied AI
• Strong Python with ML frameworks (scikit-learn, TensorFlow, PyTorch)
• Experience with NLP/LLM integration (RAG, prompt engineering, fine-tuning)
• MLOps knowledge: deployment, monitoring, versioning, CI/CD
• Cloud ML services (AWS SageMaker, Azure ML, GCP Vertex AI)
• Observability data: metrics, logs, traces; time-series and anomaly detection
• Strong English communication skills

Nice to have

• LLM-based agent architectures (LangChain, AutoGen)
• Anthropic Claude or OpenAI APIs
• IT operations or SRE background
• Graph-based dependency mapping
• Change risk prediction, automated testing

Culture & Benefits

• Strong engineering culture with consulting mindset
• Continuous focus on growth and knowledge sharing
• People-first culture

Hiring process

• CV review
• HR call
• Interview
• Client Interview
• Decision