Principal AI Architect

تكامل القابضة; Riyadh; On-site; SAR 350,000 - 550,000; Full time

Job summary

تكامل القابضة in Riyadh is seeking a Senior AI/ML Architect to own AI programs end to end, from requirements interpretation through architecture, build, integration, and go-live. You will prioritize use-case roadmaps based on business value and delivery feasibility, and act as the primary technical contact in stakeholder sessions.

You will architect the data foundation, select AI/ML approaches for each use case, design production-ready integrations with core systems, and lead hands-on

Qualifications

• 8–11 years of experience in AI/ML engineering and architecture.
• Experience owning AI delivery end to end in a lead architect capacity.
• Knowledge across NLP, MT, retrieval, LLM assistants, and forecasting.
• Experience designing ETL/ELT and lakehouse data pipelines.

Responsibilities

• Own AI dimension end to end from requirements to go-live.
• Prioritize AI use-case roadmaps based on business value.
• Act as technical lead in stakeholder sessions.
• Architect data foundation to support AI use cases.
• Design production-ready integrations with core business systems.
• Lead hands-on development and establish MLOps practices.
• Ensure governance and compliance with responsible-AI principles.

Skills

AI/ML engineering

Architecture leadership

Data pipelines design

NLP & text classification

Machine translation

Vector similarity search

LLM-based assistants

MLOps practices

Stakeholder communication

Forecasting

Regulated environments experience

Education

Bachelor's degree in Computer Science / Engineering / Data Science

Job description

Key Responsibilities

Job Description

Technical Ownership & Delivery

• Own the AI dimension of assigned programs end to end, from requirement interpretation through architecture, build, integration, and go-live.
• Prioritize and sequence use-case roadmaps based on business value and delivery feasibility, and set realistic, achievable delivery plans.
• Act as the primary technical point of contact in stakeholder and working sessions, building and maintaining technical credibility and trust.

Solution Architecture

• Architect the data foundation (ingestion, storage, quality) required to support prioritized AI use cases.
• Select and design the AI/ML approach for each use case, for example text classification, machine translation, retrieval and similarity search, LLM-based assistants or chatbots, forecasting, and decision-support scoring, based on business value and technical feasibility.
• Design integration points into core business systems so that AI outputs are production-ready and directly usable in existing workflows.

Hands-On Engineering & Delivery

• Build priority models and pipelines directly, and direct any shared or contracted engineering support assigned to a program.
• Establish MLOps practices (versioning, CI/CD, monitoring) sized appropriately to each program's scale and delivery cadence.
• Validate delivered models against agreed success metrics and produce the evidence required for stakeholder sign-off at each milestone.

Governance, Ethics & Compliance

• Ensure AI components align with responsible-AI principles and data governance and privacy requirements, with explainability and audit logging built in by design.
• Identify and elevate technical risks, gaps, and scope trade-offs promptly to relevant stakeholders and leadership.

Stakeholder Management

• Translate business and policy needs into scoped, deliverable technical work.
• Communicate scope, timeline, and resourcing trade-offs clearly, and recommend additional resourcing where a workstream's scale calls for it.

Required Qualifications

Job Requirements

• 8 - 11 years of experience in AI/ML engineering and architecture.
• Demonstrated experience owning AI solution delivery end to end, from design through production, in a lead architect or principal engineering capacity.
• Working knowledge across a range of AI/ML technique areas, such as NLP and text classification, machine translation, retrieval or vector-based similarity search, LLM-based assistants, and forecasting.
• Practical experience designing and operating data pipelines (ETL/ELT, lakehouse-style environments) to support AI use cases.
• Strong stakeholder communication, scoping, and prioritization skills, with the ability to translate business needs into technical designs and manage delivery trade-offs.
• Experience in regulated, public-sector, or specialized-domain environments is an advantage.
• Bachelor's degree in Computer Science, Engineering, Data Science, or a related field; advanced degrees are a plus.