Presales Solution Architect

Strategic Visioning

Assess and collaborate with customer CXOs and Technology Leaders in developing outcome‑driven technical transformation visions, SMART objectives, green/brown field strategies, and program charters.

Define, design, and govern the Enterprise Architecture (business, technical data, AI & security) leveraging frameworks such as TOGAF and Zachman to produce strategic blueprints.

Conduct detailed feasibility analysis (including the 6R Modernization model, Greenfield/Brownfield assessment) to define and guide MVP‑based roadmaps.

Create business cases for multi‑year programs, defining MVP‑based roadmaps and wave‑based rollouts through agile/waterfall/hybrid delivery models.

Ensure the strategic blueprint is regulatory‑compliant, covering PDPL, CCRF, NCA, GDPR, and ISO 27001.

Partner with Account Executives and Sales Leaders to drive strategic logos/accounts and establish influential customer engagement to secure contracts.

Lead customer requirements and RFI/RFP/RFQ responses to deliver end‑to‑end solutions aligned with key commercial metrics such as T2V, TTM, TCO, and xLAs.

Drive the Atos Offering Portfolios and leverage strategic global and local technology product and service partnerships.

Architectural Artifacts:
Comprehensive Atos Portfolios & Capabilities aligned to customers’ vision, business requirements, strategy architecture blueprints, and security models.

Business Cases:
Detailed business cases including Business Values, Total Cost of Ownership (TCO), and Return on Investment (ROI).

Roadmap Execution:
Definition of MVP‑based roadmaps and wave‑based rollouts.

Overall Industry

Experience:

15+ years in IT with a minimum of 5 years in senior Data, AI/ML, or Enterprise Architecture roles.

Data & AI Architecture: Ability to design end‑to‑end Data, AI/ML, and GenAI architectures, including ingestion, processing, storage, AI pipelines, model deployment, and governance.

Cloud & Data Platforms: Expertise in AWS, Azure, GCP, Hadoop, Spark, Snowflake, Databricks, and cloud‑native data services.

AI/ML & GenAI Platforms: Hands‑on knowledge of Azure ML, Sage Maker, Tensor Flow, PyTorch, Lang Chain, Jupyter, MLflow, vector databases, RAG architectures, and agentic AI platforms.

Data Platform

Skills:

Experience with Delta Lake, Kafka, Synapse, Big Query, Redshift, and other data tools.

Governance, Ethics & Compliance: Understanding of SDAIA, NDMO, PDPL, CCRF, GDPR, OECD, and ability to embed compliance into architecture design.

Integration & Orchestration: Proficiency in APIs, Microservices, Kubernetes, Docker, event‑streaming platforms, and workflow orchestration for AI pipelines.

Security & Risk Controls: Knowledge of ISO 27001, NIST, NCA, NDGP, SAMA IT, and secure‑by‑design principles for Data & AI workloads.

Industry Knowledge: Experience architecting Data & AI use cases for Government/Public Sector, Financial Services, Energy/Utilities, and Aviation, especially within the KSA landscape.

Key Platforms & Products: Exposure to regional AI ecosystems such as Sawaher Platform, FOCAL, Anything.ai, Omni Serve, and similar AI accelerators.

Data Architecture & Platform Engineering: Designing modern data platforms, lake houses, and data mesh architectures aligned with business KPIs.

Data Modernization & Migration: Transforming legacy platforms into cloud‑native, scalable, and secure data environments.

Data Governance & MDM: Implementing governance, data quality, metadata management, lineage, cataloging, and master data frameworks aligned with SDAIA/NDMO.

Analytics, BI & Insights: Building advanced dashboards, analytical models, and AI‑driven insights using ML, predictive analytics, and data science workflows.

Data Ops: Implementing CI/CD for data pipelines, monitoring, observability, and automated data quality checks for reliable operations.

GenAI & Agentic AI: Enterprise GenAI apps, RAG architectures, vector search, prompt engineering, and AI agents for task…