Lead AI Engineer (Casablanca, Hybrid)

About the role

Scale Force Cloud builds production AI systems, data platforms and cloud solutions for clients in financial services and other industries. As Lead AI Engineer in Casablanca, you own AI projects from customer discovery to reliable production delivery, stay hands-on, make architecture decisions, communicate directly with customers and help other engineers deliver high-quality work. Permanent and contract opportunities are available, with hybrid working arrangements agreed for the relevant opportunity.

Key responsibilities

• Translate customer needs into scoped solutions, delivery plans and clear technical decisions, demonstrating progress and flagging risks early.
• Build LLM applications, RAG pipelines and agent workflows with reliable tool use, APIs and business-system integrations, choosing simpler approaches when they meet the need.
• Design retrieval and data flows using SQL, PostgreSQL and vector search, improving relevance, data quality and access controls.
• Deploy and operate cloud applications with testing, CI/CD, observability and incident debugging.
• Build evaluation datasets and regression checks to improve answer quality, reliability, latency and cost.
• Protect sensitive data through application-level permissions, secure integrations, auditability and human approval.
• Review code and architecture, mentor engineers and maintain clear documentation and customer handovers.
• Depending on strengths, contribute to technical hiring, proposals, reusable demos and cloud partnerships.

Required profile

• Typically 4+ years of relevant engineering experience, with evidence of ownership more important than tenure alone.
• Hands-on delivery of an LLM application used in production, with examples of your contribution, trade-offs and lessons learned.
• Ability to lead a technical workstream, review others' work and explain complex decisions clearly to customers.
• Professional English; French is relevant for French-speaking customer engagements.

Required skills

• Strong Python and software engineering foundations: maintainable code, APIs, testing, Git and debugging.
• Experience deploying and supporting production workloads on at least one major cloud: AWS, Azure or GCP.
• Useful additional experience: AWS Bedrock or Azure AI, LangGraph or similar orchestration frameworks, Model Context Protocol (MCP), Docker and Kubernetes, financial services or regulated environments, technical interviewing, mentoring or pre-sales.

What we offer

• Ownership of production AI projects and influence over technical direction.
• Collaboration with engineers across EMEA.
• For permanent team members: professional development and certification support, coding-assistant tooling and dedicated hardware, according to the agreed package.
• Compensation discussed according to experience and scope.