Jobs at Artefact (artefact.com)

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.

Build and deploy production-grade, full-stack AI applications for clients using Gemini Enterprise and Google’s AI stack. Develop React interfaces, Python or Node.js services, agentic workflows, RAG pipelines, enterprise integrations, data pipelines, evaluations, and cloud infrastructure. Own solutions from interface through deployment, monitoring, and reliability testing. Collaborate directly with clients, support pre-sales, mentor engineers, and contribute to reusable engineering standards and accelerators.

Build and deploy full-stack AI applications, agentic systems, RAG pipelines, enterprise integrations, and production-grade OpenAI solutions. Own interfaces, backend services, data pipelines, infrastructure, evaluations, monitoring, and optimization. Deliver systems using OpenAI and Azure OpenAI, collaborate directly with clients, support presales, mentor engineers, and contribute to reusable engineering standards and accelerators.

Build and deploy production-grade, full-stack AI applications using Anthropic Claude, agentic workflows, MCP, RAG, and enterprise data integrations. Own interfaces, APIs, data pipelines, cloud infrastructure, evaluations, monitoring, and deployment. Partner directly with clients, communicate technical trade-offs, support pre-sales, mentor engineers, and establish engineering standards. The role requires strong Python and TypeScript/JavaScript skills, cloud experience, data engineering capabilities, and hands-on Anthropic ecosystem expertise.

Design, build, schedule, monitor, and optimize scalable data pipelines using Apache Airflow. Maintain reliable and secure data architecture, troubleshoot failures, document technical decisions, and provide technical leadership. Collaborate with analysts, data scientists, and engineers while mentoring team members through design reviews, pair programming, and knowledge sharing.

Supports senior consultants on data consulting projects by identifying client needs, developing strategic data recommendations, conducting workshops and training, presenting proposals, researching technology trends, and creating thought leadership content. The role involves working with clients, technology partners, and internal strategy, analytics, data, activation, and creative teams.

Lead design, development, and deployment of LLM and generative AI solutions (RAG, agentic and multi-modal systems). Architect production-ready models, evaluation frameworks, and scalable infra (serving, APIs, vector DBs). Mentor teams, manage client engagements, drive experimentation (fine-tuning, quantization, inference optimization), and contribute to thought leadership.

Join Artefact LatAm's Data & Consulting team to design and implement end-to-end analytics and ML solutions. Work across data collection, processing, EDA, model development and production, translate technical findings for business stakeholders, collaborate with consultants and engineers, and optimize models for performance and scalability under senior guidance.

As a Project Manager, you'll develop strategies, solve complex problems with data and AI, manage projects, and engage with clients to drive strategic initiatives.

Design, build and own end-to-end data solutions and infrastructure. Implement scalable pipelines using cloud and big-data technologies, optimize performance, create REST APIs and CI/CD, coach teammates, and communicate technical solutions to business stakeholders.

Develop and maintain scalable backend systems, improve system performance, collaborate with frontend developers, and support database design and optimization. Responsibilities include writing maintainable code, participating in code reviews, troubleshooting applications, documenting systems, and tracking emerging technologies. The role requires backend development experience, RESTful API and microservices knowledge, SQL and database understanding, with cloud, Docker, or Kubernetes experience preferred.

Lead AI and machine learning engineering teams delivering production-grade classical ML, LLM, and agentic systems. Own solution architecture, context and harness engineering, fine-tuning pipelines, cloud platform strategy, and technical standards. Partner with clients and senior leadership while supporting pre-sales through proposals, demos, proofs of concept, and solution scoping. Manage and mentor engineers, oversee model development, and guide scalable, reliable, cost-efficient AI deployments.