AI & Automation Engineer

Holisticon Insight is a data-focused technology and consulting company, part of the Nexer Group. They build data platforms and data-intensive systems, integrating data from multiple sources including IoT and operational systems, developing scalable data pipelines, semantic layers, and delivering analytics and AI solutions in production. They focus on clean architecture, modern tech stacks, and engineer-level ownership, providing solutions for optimizing processes, enabling better decisions, and building data products used by business teams.

• Around 5+ years of hands-on experience in enterprise automation, AI/ML engineering, platform engineering or infrastructure engineering.
• Practical experience with Python and/or PowerShell, automation/configuration-management tool such as Ansible, REST APIs, Git and Infrastructure-as-Code.
• Good understanding of GenAI/LLMs, RAG and agentic AI concepts.
• Familiarity with modern AI platforms (e.g. Azure OpenAI/Microsoft Foundry, Copilot Studio, LangChain or similar).
• Proven experience taking solutions from proof-of-concept into secure, production-grade systems.
• Ability to work across infrastructure, cloud, security and service-management teams in large enterprise environments.
• Strong English communication skills to explain technical topics to technical and business stakeholders.

Nice to have:

• Microsoft Azure/AI certifications.
• ITIL experience.
• SRE/AIOps experience.
• ServiceNow/ITSM exposure.

• Design and build AI assistants, agents and automation that remove manual work and improve enterprise operations.
• Turn operational pain points into reusable solutions using GenAI/LLMs, agentic AI, APIs, workflows, scripts and Infrastructure-as-Code (e.g. Ansible, Terraform, Python/PowerShell).
• Use RAG/Agentic RAG, Copilot-style assistants and modern orchestration frameworks to ground AI in enterprise knowledge and connect it to real systems (e.g. ServiceNow, Microsoft/Azure, infrastructure platforms).
• Apply AIOps practices including anomaly detection, event correlation, predictive insights and safe, guardrailed self-healing/automated remediation.
• Set guardrails for AI agents: access control, approvals, human-in-the-loop decisions and auditability.
• Take solutions from proof-of-concept to secure, supportable production with testing, observability and documentation.
• Collaborate closely with cross-functional teams (infrastructure, network, security, workplace, service management, architecture) and translate technical work into business outcomes.

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