Business Systems & AI Architect

Nexthink is the leader in digital employee experience management software. The company provides IT leaders with unprecedented insight allowing them to see, diagnose and fix issues at scale impacting employees anywhere, with any application or network, before employees notice the issue. As the first solution to allow IT to progress from reactive problem solving to proactive optimization, Nexthink enables its more than 1,300 customers to provide better digital experiences to more than 18 million employees. Dual headquartered in Lausanne, Switzerland and Boston, Massachusetts, Nexthink has 9 offices worldwide.

Role Overview

We are looking for a Business Systems & AI Architect to reimagine and evolve Nexthink’s internal technology landscape.

This role goes beyond traditional architecture: you will challenge how our systems work today, identify opportunities to simplify, modernize, and augment them with AI, and help transition from a fragmented SaaS stack to a cohesive, intelligent, and scalable architecture.

A critical part of this role is shaping our data foundation, ensuring that our data platform and warehouse enable both business insights and AI-driven use cases.

Sitting at the intersection of business, IT, and AI, you will work across the organization to deeply understand how teams operate today and design how they should operate tomorrow.

Responsibilities

Assess the current tech stack and identify opportunities to simplify, consolidate, or replace systems; Lead the evolution toward a modern, AI-enabled architecture, reducing tool sprawl and operational complexity; Define target architecture principles and drive migration from legacy patterns to scalable platforms; Evaluate SaaS solutions not only for fit, but for their ability to integrate into a broader, data-driven ecosystem; Define and drive the implementation of a scalable data platform / data warehouse (e.g., Microsoft Fabric or equivalent); Ensure data from SaaS and internal systems is centralized, structured, and accessible; Establish data models, governance, and ownership to support both analytics and operational use cases; Enable a single source of truth for reporting, decision-making, and AI applications; Partner with teams to ensure data is reliable, well-understood, and usable across the organization; Identify and implement AI use cases that fundamentally improve how teams work, not just incremental enhancements; Design architectures that embed AI into workflows (Copilot, agents, automation), making it part of the operating model; Leverage the data platform to power AI models, copilots, and decision systems; Define patterns for AI orchestration, data access, and agent interoperability; Partner with teams to rethink processes through the lens of AI-first design; Design end-to-end system architectures across SaaS, internal platforms, and data layers; Define scalable integration patterns (APIs, event-driven, orchestration layers); Ensure interoperability and reduce silos across business systems; Enable real-time and batch data flows into the data platform; Engage with stakeholders across all functions to understand how work actually happens; Translate business challenges into scalable, reusable system designs; Challenge existing processes and assumptions to unlock better ways of operating; Act as a trusted advisor to both technical and non-technical stakeholders; Establish lightweight governance to ensure security, scalability, and maintainability; Define standards across SaaS, data, and AI usage; Balance speed of innovation with long-term sustainability; Drive adoption of standards without slowing down teams

Requirements

Strong experience in enterprise architecture, SaaS ecosystems, and cloud platforms (Azure preferred); Proven experience designing or implementing a data warehouse / modern data platform; Solid understanding of data modeling, ETL/ELT pipelines, and data governance; Hands-on understanding of AI/ML ecosystems and enterprise AI tools (e.g., Azure AI, Copilot, LLM-based agents); Proven experience simplifying or transforming complex tech stacks; Solid expertise in integration patterns, APIs, and middleware (e.g., Mulesoft or equivalent); Experience with identity and access management (SSO, SCIM, Conditional Access); Strong grasp of security and compliance principles; Systems thinker who understands that data is the backbone of modern architecture and AI; Ability to connect business processes, systems, and data into a coherent whole; Comfortable operating across all levels of the organization, from engineers to executives; Comfortable challenging the status quo and proposing non-obvious solutions; Pragmatic and impact-driven: focused on what actually moves the needle; Strong communication skills, able to translate complexity into clarity