Lead AI Products Architect

Emdad By Elm; Riyadh; On-site; SAR 550,000 - 700,000; Full time

Job summary

Emdad By Elm seeks a senior hands-on AI technical leader embedded in the AI Products Management Department. You will translate product intent into scalable AI system designs, collaborating closely with Product Managers, AI Research, and Delivery teams to ensure measurable, reliable, and commercially viable production solutions.

You will own end-to-end architecture, model evaluation, data readiness, and MLOps requirements, acting as the technical backbone of AI products while guiding risk

Qualifications

• Experience leading AI product architecture and technical design for GenAI/ML systems.
• Ability to define evaluation metrics, data readiness, and governance for production AI.
• Collaboration with product managers, researchers and delivery teams.

Responsibilities

• Own end-to-end AI product architecture and technical design, including inference services and data pipelines.
• Define reference architectures, reusable components, and guardrails for production systems.
• Lead design reviews with Engineering, Platform, and Security teams to ensure scalability and cost efficiency.
• Define evaluation strategies, success metrics, and ML objectives for product success.
• Mentor PMs on AI fundamentals and translate product needs into non-functional requirements.

Skills

AI product architecture

Technical design

Model evaluation

Data strategy

AI operations

Technical leadership

Tools

MLOps platforms

Vector databases

Job description

Role Summary

We seek a senior hands-on AI technical leader embedded within the AI Products Management Department. This role partners closely with Product Managers to translate product intent into scalable, secure, and production-ready AI system designs. Collaborate with the AI Research Team and the Delivery Team, the Lead AI Products Architect owns the technical quality bar across the AI product lifecycle – covering architecture, model performance, data readiness, and operational excellence. This role does not replace Engineering or Research. Instead, it acts as the technical backbone of AI Products, ensuring solutions are measurable, reliable, and commercially viable in production.

Key Responsibilities

1 - AI Product Architecture & Technical Design

• Own end-to-end technical architecture for AI products (GenAI, RAG, Agents, and ML), including inference services, orchestration, data pipelines, APIs, and integrations.
• Define reference architectures and reusable components (RAG modules, evaluation frameworks, prompt/versioning, feature stores, vector DB patterns, guardrails).
• Lead design reviews with Engineering, Platform, and Security teams to ensure scalability, resilience, cost efficiency, and maintainability.

2 - Model Performance Criteria and Evaluation

• Define product-specific success metrics and acceptance criteria (accuracy, groundedness, latency, cost, safety, robustness, drift).
• Design offline and online evaluation strategies, e.g. A/B testing.
• Own the AI evaluation playbook (hallucination detection, retrieval quality, safety, jailbreak resistance; ML metrics such as precision/recall and calibration).

3 - Data Strategy & Readiness

• Own AI product data strategy: sources, contracts, quality checks, lineage, governance, privacy-by-design.
• Define data readiness gates across PoC, MVP, and Scale phases.
• Partner with Data Engineering on pipelines and continuous data quality monitoring.

4 - AI Operations

• Specify MLOps/LLMOps requirements: model registry, CI/CD, prompt/config versioning, observability, monitoring, rollback strategies.
• Define runtime controls including guardrails, policy enforcement, red-teaming, rate limiting, and audit logging.

5 - Technical Leadership

• Act as technical co-pilot to Product Managers: translate product requirements into system constraints and non-functional requirements.
• Identify risks early and propose pragmatic trade-offs.
• Mentor Product Managers on AI technical fundamentals