AI Engineer

Location:
On-Site, Abu Dhabi Work Type: Full-time, 5 days a week Compensation: PHP 140,000
- 200,000/Month (still negotiable depending on skills and experience) Role Summary The AI Engineer is responsible for designing, building, and deploying AI and machine learning solutions that solve business problems and enhance operational intelligence across MSTS. The role focuses on the end-to-end development, integration, and lifecycle management of AI models, including predictive, generative, and agentic use cases, embedded within MSTS enterprise systems. By integrating AI with existing systems, the role ensures that big data available within MSTS fleet is used proactively to solve business problems, optimize performance, and enhance analytics capabilities supporting operational efficiency, and business growth.

Key Responsibilities

- Design, build, and deploy AI solutions across MSTS functions and operations, translating business problems into production-grade technical implementations.
- Develop and operationalise AI and machine learning models, including predictive, classification, forecasting, and generative AI use cases.
- Develop and maintain Retrieval-Augmented Generation (RAG) evaluation frameworks and performance metrics to ensure AI model outputs meet accuracy, relevance, reliability, and safety requirements.
- Develop agentic AI workflows that integrate LLM reasoning, external tools, and enterprise data sources to automate and support complex business tasks.
- Engage with vendors during proof-of-concept (PoC) phases to evaluate AI solutions, technical capabilities, and business fit.
- Convert PoC prototypes from third-party AI vendors into scalable, integrated, and supportable production solutions within the MSTS environment.
- Maintain awareness of the evolving AI landscape, including foundation models, agentic AI frameworks, and asset performance AI solutions, and recommend adoption where clear business value can be demonstrated. AI Engineering & Model Development
- Support end-to-end AI solution deployment from prototype to production within enterprise systems.
- Integrate AI solutions with the MSTS enterprise stack, including ERP, EAM, APM, document management systems, and corporate productivity platforms (Microsoft 365, SharePoint, Teams, etc.) in addition to SCADA systems, and other IoT platforms.
- Deploy, test, and maintain machine learning models in production environments.
- Implement MLOps practices, including model monitoring, versioning, lifecycle management, and performance tracking.
- Monitor, troubleshoot, and optimize deployed models to ensure high performance, stability, and reliability. AI Deployment & MLOps/Integration
- Support end-to-end AI solution deployment from prototype to production within enterprise systems.
- Integrate AI solutions with the MSTS enterprise stack, including ERP, EAM, APM, document management systems, and corporate productivity platforms (Microsoft 365, SharePoint, Teams, etc.) in addition to SCADA systems, and other IoT platforms.
- Deploy, test, and maintain machine learning models in production environments.
- Implement MLOps practices, including model monitoring, versioning, lifecycle management, and performance tracking.
- Monitor, troubleshoot, and optimize deployed models to ensure high performance, stability, and reliability. Process Analysis & Collaboration
- Partner with business function owners to identify, qualify, and prioritize AI use cases, applying value-versus-effort assessment and clear success criteria.
- Translate functional requirements into technical specifications, data requirements, and solution architecture; define KPIs and acceptance criteria prior to development.
- Run structured PoCs with defined hypotheses, datasets, and exit criteria, and provide evidence-based recommendations to scale, pivot, or discontinue initiatives.
- Work with the O&M team to align AI models with reporting, dashboards, and predictive maintenance objectives, ensuring accuracy and operational relevance.
- Contribute to the MSTS AI roadmap, including vendor assessments and build-versus-buy recommendations.
- Collaborate with data scientists and other engineers to integrate AI solutions into broader system architectures and enterprise platforms.
- Stay current with AI trends, emerging technologies, and industry best practices, and proactively suggest improvements to existing systems, models, and workflows. Compliance, Governance & Support
- Ensure all AI solutions comply with Masdar/MSTS information security, data privacy, data classification, and acceptable-use policies, as well as applicable regulations in operating jurisdictions.
- Implement controls for handling sensitive enterprise data in AI systems, including commercial and contractual information, ensuring confidentiality requirements are strictly maintained.
- Maintain comprehensive technical documentation for each solution, including architecture diagrams, data flow diagrams, API documentation, user guides, and change logs.
- Support internal and external audits by providing evidence of access controls, model validation, change management, and decision logs.
- Manage third-party AI vendors from a technical delivery perspective, including reviewing SOWs, validating technical claims, running vendor PoCs, and ensuring alignment with MSTS architectural and security standards.
- Conduct knowledge transfer sessions and develop training materials to enable business users and internal teams to independently operate, monitor, and troubleshoot solutions. Compliance with information security policies, procedures, and requirements always
- Adhere to any applicable Masdar information security policies and procedures and identify and report security incidents and suspected weaknesses to the appropriate point(s) of contact.
- Protect assets under care (e.g., laptops and other devices) and information/credentials against unauthorized access, sharing, and/or damage/loss in accordance with the Information Classification and Handling Procedure.
- Clear desks of all sensitive material and log off/lock workstations at the end of the day and when leaving the desk for a prolonged period in accordance with Acceptable Usage Policies.
- Ensure that no software is installed, copied, or modified on Masdar/MSTS equipment without authorization. Support Quality Health and Safety Environment (QHSE) activities, Masdar policies, objectives, and compliance with the laws and regulations of the country where the projects are located.
- This includes participating (when requested) in QHSE audits, office inductions, incident reporting, and review of QHSE performances as applicable. Qualifications, Experience, & Skills Preferred Qualifications
- Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, Electrical Engineering, or a related field. Preferred Experience
- 3–5 years of experience in AI/ML engineering or applied machine learning roles, with demonstrable experience deploying AI models in production environments.
- Proven experience deploying Generative AI / LLM-based applications in enterprise environments.
- Hands-on experience with MLOps tools such as MLflow, Azure ML Studio, or equivalent platforms for experiment tracking, model versioning, and deployment pipelines. Familiarity with LLM orchestration frameworks (e.g., LangChain, LangGraph, or LlamaIndex) and vector database technologies (e.g., Pinecone, Weaviate, Qdrant, or Azure AI Search) is strongly preferred.
- Strong hands-on experience with Python and ML libraries such as TensorFlow, PyTorch, or Scikit-learn.
- Exposure to operational technology (OT) environments, including SCADA systems, IoT sensor data, and time-series data streams from industrial assets, is a strong advantage.
- Experience with modern LLM frameworks and vector databases.
- Strong experience with SQL, APIs, and data engineering workflows.
- Experience with cloud platforms such as AWS, or Azure.
- Strong understanding of time-series data, predictive analytics, and anomaly detection techniques.
- Ability to translate complex business problems into clear technical requirements and scalable AI solutions.
- Experience collaborating with cross-functional teams, including engineers, data scientists, and business stakeholders.
- Strong communication skills with the ability to present technical concepts to non-technical audiences. Languages Proficiency in English Pay: Php140,000.00
- Php200,000.00 per month

Benefits:
- Company events
- Life insurance
- Opportunities for promotion Application Question(s):
- Do you have any experience using MLOps Tools?
- Do you have any experience using LangChain, LangGraph, or LlamaIndex?

Education:
- Bachelor's (Preferred)

Experience:
- AI/ML Engineering: 3 years (Required) Work

Location:
In person