Top Tech Jobs & Startup Jobs

Designs Data and AI operating models, Centers of Excellence, cloud and Databricks architectures, governance frameworks, and GenAI platforms. Translates business requirements into governed data products, evaluates vendors and technology choices, and oversees implementation quality, risks, and rollout. The role combines strategy consulting, enterprise architecture, Data Mesh, GenAI, operating model design, business cases, and portfolio governance.

Own full-cycle technical and consulting recruiting across the Americas, partnering with hiring managers to define needs, source candidates, manage pipelines, and deliver offers. Lead campus recruiting and university partnerships while improving recruiting processes, structured interviews, employer branding, reporting, and candidate experience. Use recruiting metrics, AI tools, and market insights to strengthen talent strategies and hiring outcomes.

Leads employee relations, manager advisory, talent development, onboarding, employee experience, benefits administration, immigration, and global mobility across North America. Advises leaders, coaches managers, develops People programs, supports performance and talent reviews, uses People data for decision-making, and partners on compensation, job architecture, recruiting, and organizational improvement. The role also builds scalable HR processes and supports global People initiatives.

Supports clients with advanced data analysis, AI strategy, recommendations, and presentations. Builds AI-assisted prototypes, automations, and internal tools using Claude Code, Gemini CLI, or Codex. Applies GenAI concepts such as prompting, RAG, agents, and context engineering, while coordinating project efforts and contributing to proposals and thought leadership.

Provide data and technology consulting services, using analytics, artificial intelligence, and Big Data to solve client business challenges. Collaborate with consultants, scientists, engineers, and analysts; collect, organize, and analyze data; develop strategic recommendations; implement data-driven solutions; present insights to clients; manage priorities and deadlines; identify risks; and contribute to team training and strategic content.

Leads Artefact’s Google Cloud sales practice across the Americas, owning the Google relationship, co-sell motion, pipeline, presales, and deal closure. Advises executive clients on AI strategy, packages Gemini Enterprise and Google Cloud offers, builds partner-funded opportunities, and develops a certified consulting team. The role combines executive selling, alliance management, hands-on AI prototyping, offer development, recruiting, and practice profitability ownership.

Lead and grow Artefact’s consulting business in Romandie by expanding client relationships, winning new accounts, building the Lausanne team, and guiding executives through data and AI transformations. The Partner will own go-to-market strategy, pipeline, proposals, pricing, client satisfaction, project margins, staffing, hiring, and team development while contributing sector expertise across industry, retail, consumer, and luxury markets.

Coordinate LatAm marketing operations across CRM lifecycle management, paid media, AI-driven workflows, content strategy, and funnel analytics. Design automation and nurturing campaigns, manage LinkedIn and Google Ads, coordinate agencies, produce content, analyze performance using GA4 and Looker Studio, and make autonomous growth decisions. The role requires broad marketing experience, strong writing, CRM and automation expertise, practical AI usage, data fluency, and advanced English.

Design, build, schedule, monitor, and optimize scalable data pipelines using Apache Airflow and cloud and big-data technologies. Collaborate with analysts, scientists, and engineers to ensure reliable, secure data delivery. Troubleshoot failures, maintain data architecture, document technical decisions, lead solution implementation, and mentor team members through coaching, pair programming, and design reviews.

Build and deploy full-stack AI applications, including React interfaces, Python or Node services, agentic systems, RAG pipelines, data pipelines, evaluations, and cloud infrastructure. The role requires production engineering practices, AI platform expertise, client communication, pre-sales support, and mentoring junior engineers.