Technical Project Manager

^{The TPM will play a key role in overseeing the end-to-end delivery of AI, analytics and software engineering projects, from model development, data pipeline integration, dashboard creation, API development and backend services development. Reporting to the Technical Program Manager, you will be responsible for managing project scope, schedule, budget, risk and quality, and ensuring the cross-functional team of engineers and data scientists adhere to best practices in software architecture, code quality, testing and deployment.}

^{Key Responsibilities}

^{Project Planning & Execution}

• ^{Create detailed project plans covering AI/ML workstreams, software architecture design, UI/dashboard development, APIs, and infrastructure.}
• ^{Track milestones—POCs, MVPs, QA cycles, UAT, production roll‑outs—and drive on‑time, on‑budget delivery.}

^{Technical Leadership & Software Engineering}

• ^{Decompose high‑level objectives into technical work packages: data‑ingestion jobs, model training, microservices, frontend dashboards.}
• ^{Lead architecture reviews, ensure coding standards, automated testing (unit/integration), and CI/CD pipelines.}
• ^{Coach teams on design patterns, RESTful API best practices, scalable database/schema design, and cloud‑native deployments.}

^{Cross‑Functional Coordination}

• ^{Facilitate agile ceremonies (stand‑ups, sprint planning, backlog grooming, retrospectives) across software and data teams.}
• ^{Coordinate handoffs between UI/UX designers, frontend developers, backend engineers and DevOps to maintain smooth integration.}

^{Stakeholder & Vendor Management}

• ^{Act as liaison with product owners, domain experts, external software/consulting vendors.}
• ^{Present technical status—burn‑down charts, release plans, quality metrics—to leadership and stakeholders.}

^{Risk & Issue Management}

• ^{Identify both AI‑specific (data drift, model performance) and software‑specific (security, scalability, tech‑debt) risks.}
• ^{Maintain risk logs, propose mitigation strategies, and escalate critical issues.}

^{Quality Assurance & Compliance}

• ^{Ensure code reviews, automated testing coverage, and performance testing are in place.}
• ^{Oversee system‑integration testing, UAT, and ensure compliance with security standards (ISO, API).}

^{‍Required Skills & Experience:}

• ^{Bachelor’s in Computer Science, SoftwareEngineering, or related.}
• ^{3+ years managing software engineering, AI, or dataanalytics projects in Oil & Gas or similar heavy industries.}
• ^{Demonstrated success in managing and aligning diversestakeholders.}
• ^{Communication: Articulate technical concepts—architecture diagrams,code‑quality metrics—to both technical and non‑technical audiences.}
• ^{Analytical: Extract insights from performance metrics, errorrates, and project KPIs to drive continuous improvement.}
• ^{Problem‑Solving: Quickly diagnose system failures, code regressions,and data‑pipeline issues, and lead resolution.}
• ^{Deep expertise in Agile methodologies (Scrum, Kanban) and a solidgrasp of Waterfall practices.}
• ^{Hands-on experience with tools such as Jira, Confluence, CI/CD pipelines (e.g., Jenkins, GitLab CI), and cloud platforms (OCI, GCP).}
• ^{Solid understanding of the architectural and operational differences between cloud-native and on-premises software environments.}
• ^{Fluent in both Arabic and English a must.}
• ^{Must be eligible and authorized to work in the Kingdom of Saudi Arabia (KSA).}

^{Preferred Qualifications:}

• ^{Certification in Project Management Professional(PMP), Agile Project Management, PRINCE2, or Scrum Master (CSM or equivalent).}
• ^{Master’s in Software Engineering, Data Science, or ProjectManagement.}
• ^{Experience with containerization (Docker/Kubernetes),microservices, and infrastructure-as-code (Terraform).}
• ^{Domain knowledge in refinery automation, LLMs or digital‑twins.}
• ^{Familiarity with SCADA, PI System, or SAP integrations.}