Jobs at Artefact (artefact.com)

Lead finance, people and operations for Artefact Abidjan: internalise bookkeeping, payroll and reporting; manage cash flow, compliance and mission profitability; run end-to-end recruitment, evaluations and HR compliance; support sales ops, staffing and client onboarding. Build processes, protect culture, and scale the office toward COO responsibilities.

Design, build, and maintain scalable data pipelines and workflows on GCP. Contribute across the project value chain, including infrastructure, data collection, machine learning models, REST APIs, front-end and back-end development, testing, and continuous deployment. Collaborate with diverse teams, communicate technical concepts to business stakeholders, troubleshoot complex issues, prioritize work, meet deadlines, and mentor team members.

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.

Lead North America People strategy for the US and Canada, building scalable HR operations and talent programs. Own recruiting, workforce planning, employee relations, performance, compensation, benefits, immigration, L&D, policy, and HR ops while partnering with senior leaders and regional teams to support a rapidly scaling AI/data consulting business.

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.

Manage and improve distributed IT infrastructure across the Americas, including Jamf-managed macOS and Windows device fleets, identity platforms, GCP and Azure environments, security controls, SaaS tools, and vendor licensing. Automate recurring operations with scripting and APIs, optimize cloud costs, support incidents, maintain documentation, and lead IT initiatives from proposal through implementation while communicating risks and progress to technical and non-technical stakeholders.

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.

Own end-to-end data science and AI solutions, from business problem framing through production deployment and monitoring. Build statistical and machine learning models for forecasting, classification, clustering, and causal analysis; conduct LLM fine-tuning and evaluation experiments; develop data pipelines, dashboards, and evaluation suites; and advise clients on AI architecture decisions. Present findings to nontechnical stakeholders and mentor junior data scientists.

Lead client-facing data and AI consulting engagements through discovery, advanced analysis, strategic recommendations, presentations, and project coordination. Use AI tools and agentic coding platforms to build prototypes, automations, and analyses. Apply GenAI concepts, develop expertise in major AI ecosystems, support proposals and thought leadership, and mentor junior consultants and interns.

Manages AI and data consulting projects, including planning, delivery, quality, client relationships, and team development. Translates client needs into strategic recommendations, prototypes solutions with AI coding tools, and applies concepts such as RAG, semantic layers, MCP, and context engineering. Coaches consultants in AI-native workflows, supports executive communications, contributes to proposals and business development, and helps expand client engagements.

Lead and grow Artefact’s U.S. Life Sciences practice through business development, client relationship ownership, consulting delivery, and practice building. Develop pipelines, win engagements, advise senior pharmaceutical stakeholders, and oversee commercial analytics, data strategy, AI use cases, and insights transformation projects. Guide multidisciplinary consulting, data science, and engineering teams while shaping offerings, methodologies, thought leadership, and talent development.

Leads Artefact’s US AI and data consulting practice by advising C-level clients, winning engagements, shaping transformation strategies, and delivering production-grade AI solutions. The role manages multidisciplinary teams, develops consultants, prototypes with agentic coding tools, guides clients from GenAI pilots to governed adoption, builds platform expertise, contributes to thought leadership, and grows the commercial pipeline and client portfolio.

Build and deploy full-stack AI applications, including React interfaces, Python or Node.js services, agentic workflows, RAG pipelines, data integrations, evaluations, and cloud infrastructure. Ensure production reliability through testing, monitoring, CI/CD, observability, and infrastructure as code. Work directly with clients, support pre-sales, mentor junior engineers, and contribute to reusable engineering accelerators.

Lead marketing measurement and effectiveness programs using marketing mix modeling, incrementality testing, attribution, causal inference, experimentation, and optimization. Own statistical methodology, production deployment, GenAI applications, client relationships, executive communication, team development, and account growth. Translate models into budget and media decisions, build reusable measurement accelerators, uphold scientific rigor, and remain hands-on with technical problem-solving, MLOps, cloud industrialization, and model review.

Lead design and delivery of end-to-end AI/ML solutions: define architectures, run PoCs and pilots (LLMs/GenAI, RAG, fine-tuning), build and deploy models, implement MLOps/LLMOps on cloud platforms, enforce security and governance, advise clients, mentor teams, and support pre-sales and thought leadership.

Manage end-to-end staffing: align consultants to projects, monitor capacity and utilization, maintain resource data and systems, produce resource metrics, partner with recruiting and finance for workforce planning, and improve staffing processes to support consultant development and business goals.

Full-cycle talent acquisition contract role owning intake through offer and onboarding for consulting and technical roles. Source proactively, screen candidates, manage interviews, partner with hiring managers, maintain pipelines and recruiting data, and improve recruiting processes and reporting.