AI Architect

Employer OverviewThe company is a pioneering global AI-enhanced research company that transforms how businesses access, analyze, and act on critical intelligence. They have evolved from traditional business research outsourcing to become the strategic partner that combines cutting-edge artificial intelligence with deep human expertise. They offer 3 services to their global clients (leading consulting companies, Fortune 500 companies, and government entities): AI and Data Advisory, Next-Gen Insights, and Resource Scaling.Job SummaryThis role will give you the opportunity to design and shape the technical foundation of our Analytics & AI practice, working on high-impact client engagements across industries. As our Analytics & AI Architect, you will sit at the intersection of data engineering, analytics, data science, and AI, defining the standards, frameworks, and architectures that our teams build upon.Key Responsibilities:You will lead the technical architecture of Data, Analytics, and AI solutions for our clients, covering the full lifecycle from design to deployment:Architecture & DesignDesign end-to-end data architectures: data lakes, lakehouses, warehouses, and streaming pipelines.Define standards for data modeling, storage, ingestion, and transformation across client engagements.Architect MLOps and AI deployment infrastructure (model registries, CI/CD for ML, monitoring). ● Lead technical decisions on cloud platforms (Azure, AWS, GCP) and open-source tooling.Team Enablement Define best practices and reusable frameworks for data engineers, analysts, and data scientists.Act as a technical mentor and reviewer for cross-functional project teams.Bridge the gap between data analysts, data engineers, and AI/ML engineers on complex projects. Contribute to internal knowledge base, toolkits, and delivery accelerators.Client EngagementLead architecture workshops and discovery sessions with client stakeholders.Translate business requirements into scalable, robust technical blueprints.Present architecture decisions to both technical teams and executive audiences.Support pre-sales and proposal efforts with technical scoping and solution design.OtherProvide internal training and knowledge-sharing sessions with the team.Support the Head of Practice on business development and internal capability initiatives.QualificationsEducation & Professional Experience: Bachelor's Degree in Computer Science, Data Engineering, Software Engineering, Applied Mathematics, or a related field.Full proficiency in English + 1 additional language (French, Arabic, Spanish, German...).6+ years of technical experience in data architecture or a closely related field.Proven track record in a consulting or multi-client services environment.Technical Skills:Data Architecture & Platforms Proven hands-on experience designing large-scale data platforms: data lake, lakehouse, or warehouse architectures (Databricks, Snowflake, BigQuery, Azure Synapse, Redshift).Strong command of SQL and at least one of Python, Scala, or Spark for data processing and transformation.Experience with Big Data ecosystems: Hadoop, Spark, PySpark, Hive, or equivalent.Familiarity with streaming and real-time architectures (Kafka, Flink, Spark Streaming).AI & ML InfrastructureProven hands-on experience with ML lifecycle tooling: MLflow, Kubeflow, SageMaker, Azure ML, or equivalent.Experience architecting MLOps pipelines: model versioning, CI/CD for ML, monitoring and drift detection.Exposure to GenAI and LLM integration patterns (RAG architectures, vector databases, prompt pipelines).Data Engineering & DeploymentProven hands-on experience with orchestration and transformation tools: Airflow, dbt, or equivalent.Proven hands-on experience with container technologies: Docker, Kubernetes.Proven hands-on experience with versioning software: Git, GitHub, GitLab.Proven hands-on experience deploying solutions in cloud ecosystems: AWS, Azure, or Google Cloud.Governance & StandardsKnowledge of data governance frameworks: data catalogs, lineage tracking, access control, and data quality management.Exposure to BI and data visualization platforms (Power BI, Tableau, Looker) and semantic layer design.Interpersonal SkillsAbility to step back, analyze complex problems, define architectural options, and drive decisions. Strong ability to work and collaborate with a variety of stakeholders across technical and business functions.Excellent communication skills with the ability to translate complex technical architectures into clear business implications.High autonomy, attention to detail, and ability to manage multiple client engagements simultaneously.