Senior Artificial Intelligence Operations Engineer

• Salary: up to 22 500 PLN

• Type of contract: UoP

• Working model: Remote

Join our client, which makes software to help users organize data, discover the truth, and act on it. Their SaaS product manages large volumes of data and quickly identifies key issues during litigation and internal investigations. The AI-powered communication surveillance product proactively detects regulatory misconduct like insider trading, collusion, and other non-compliant behavior. They have over 300,000 users in 49 countries serving thousands of organizations globally.

Position Summary:

We are looking for a Senior AIOps Engineer to spearhead the design and deployment of AI-powered solutions aimed at improving the performance and reliability of our critical systems. In this role, you will be responsible for building scalable AI infrastructure, implementing machine learning models for forecasting and analysis, and integrating observability tools to enable proactive system monitoring and issue resolution.

Key Responsibilities:

• AI/ML Solutions for IT Operations: Develop and apply artificial intelligence and machine learning techniques to enhance IT operations through automation, including capabilities like anomaly identification, event matching, and predictive analysis.

• Enhancing System Observability: Partner with various technical teams to embed observability tools (such as Prometheus and Grafana) into AIOps ecosystems, supporting real-time system visibility and proactive issue resolution.

• Operational Automation: Create and deploy automation frameworks and scripts using technologies like Terraform, Ansible, and CI/CD pipelines to simplify routine operational activities.

• Smart Incident Response: Leverage AI-powered insights to boost the efficiency of incident recognition, diagnose root causes faster, and reduce resolution times, ultimately improving service dependability.

• Data Insights & Optimization: Examine vast datasets from IT operations to uncover insights, trends, and continuous improvement opportunities across infrastructure and services.

• Team Collaboration: Work in close coordination with SRE, observability, and product teams to ensure AIOps efforts are aligned with business objectives and integrated effectively across environments.

• Interdepartmental Cooperation: Collaborate with data science teams to exchange knowledge, align on strategy, and contribute to broader machine learning initiatives within the company.

• Support for MLOps: Maintain awareness of current MLOps efforts and communicate updates within the team to help transition AI models into production environments.

• Innovation & Prototyping: Research and develop proof-of-concept AI/ML solutions aimed at driving operational excellence and process innovation.

Required Qualifications:

• Bachelor’s or Master’s degree in Computer Science or related discipline.

• A minimum of 4 years in DevOps or software engineering, including 2+ years dedicated to AIOps or AI/ML applications in operational contexts.

• At least 2 years of practical experience in machine learning, ideally in large-scale data environments.

• Strong programming skills in languages such as Python, Java, or C#.

• Experience working with observability platforms like the Grafana stack.

• Hands-on expertise with cloud-native architectures and major cloud providers (AWS, Azure, or GCP), including tools like Docker and Kubernetes.

• Solid understanding of infrastructure-as-code and automation tooling.

• Background in site reliability engineering, especially in combining operational metrics with intelligent systems.

• Excellent analytical thinking, strong communication skills, and a team-oriented mindset.

Preferred Qualifications:

• Prior experience with AIOps tools like BigPanda, Moogsoft, or Keep.

• Familiarity with MLOps tools and best practices.

• Knowledge of machine learning frameworks such as PyTorch or TensorFlow.

Benefit Highlights:

• Comprehensive health, dental, and vision plans

• Parental leave for primary and secondary caregivers

• Flexible work arrangements

• Two, week-long company breaks per year

• Unlimited time off

• Long-term incentive program

• Training investment program