ai expert for plant data model (pdm project)

oas team lead (oracle analytics server & bi delivery activities) arabic speaker

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ai expert for plant data model (pdm project) Jobs in Qatar

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civil 3d bim modeler

ai expert for plant data model pdm project

Al Adyat consultancy

Job Profile: AI Expert for Plant Data Model (PDM Project)Job SummaryWe are seeking a highly skilled AI Expert to design, build, and operationalize AI/ML solutions that deliver measurable business outcomes. The ideal candidate combines deep machine learning expertise with strong software engineering practices, MLOps proficiency, and stakeholder collaboration. This role will lead end-to-end projects&mdash;from problem framing and data acquisition to model development, deployment, monitoring, and continuous improvement&mdash;while ensuring compliance with security, privacy, and governance policies.Key Responsibilities&middot; Partner with business stakeholders to translate strategic objectives into AI use cases with clear KPIs and ROI.&middot; Own the full ML lifecycle: data sourcing, feature engineering, model selection, training, evaluation, and production deployment.&middot; Implement robust MLOps: CI/CD for ML, model registry, automated testing, reproducible pipelines, and monitoring (drift, performance, fairness).&middot; Design scalable data/feature pipelines using best practices for data quality, lineage, and governance.&middot; Develop models across domains (e.g., predictive analytics, time series, NLP, computer vision, recommender systems).&middot; Optimize models for efficiency and cost across CPU/GPU, leveraging quantization, distillation, or serving optimizations.&middot; Deploy and maintain models on cloud and on-prem platforms; orchestrate with containers and microservices (Docker/Kubernetes).&middot; Establish and enforce responsible AI practices: privacy-preserving methods, bias detection/mitigation, explainability, and secure handling of data.&middot; Produce high-quality documentation: design docs, runbooks, experiment logs, and user guides; present results to technical and non-technical audiences.&middot; Mentor engineers and analysts; contribute to standards, templates, and reusable components within the AI platform.Minimum Qualifications&middot; Bachelor&rsquo;s degree in computer science, Data Science, Engineering, Mathematics, or related field (or equivalent experience).&middot; 5+ years building and deploying ML models in production environments.&middot; Strong programming skills in Python and experience with ML frameworks (e.g., scikit-learn, TensorFlow, PyTorch).&middot; Hands-on experience with data processing frameworks (e.g., Pandas, Spark), SQL/NoSQL databases, and feature stores.&middot; Proficiency in MLOps tooling (e.g., MLflow, DVC, Kubeflow, Airflow) and CI/CD for ML.&middot; Experience deploying to cloud platforms (e.g., Azure Machine Learning, AWS SageMaker, GCP Vertex AI) and container orchestration (Docker/Kubernetes).&middot; Solid understanding of statistics, experiment design (A/B testing), and model validation techniques.&middot; Excellent communication and stakeholder management skills; ability to articulate complex concepts clearly.Preferred Qualifications&middot; Master&rsquo;s or PhD in a quantitative field.&middot; Experience with NLP (transformers, LLMs, RAG) and computer vision (CNNs, detection/segmentation).&middot; Exposure to time-series forecasting, optimization, and reinforcement learning for industrial use cases.&middot; Experience with Azure ecosystem (Azure ML, Databricks, Data Factory, Synapse) and enterprise integration patterns.&middot; Familiarity with privacy-preserving techniques (differential privacy, federated learning) and model interpretability (SHAP, LIME).&middot; Track record of delivering AI solutions in manufacturing, energy, or operations (e.g., predictive maintenance, process optimization).Technical Stack &amp; Tools&middot; Languages: Python (preferred), SQL; familiarity with C++/Java is a plus.&middot; ML/AI: scikit-learn, TensorFlow, PyTorch, XGBoost, Hugging Face; experiment tracking (MLflow).&middot; Data: Pandas, Spark, Delta/Parquet; data versioning (DVC); feature stores.&middot; Pipelines &amp; Orchestration: Airflow, Prefect, Kubeflow; Docker/Kubernetes for serving.&middot; Monitoring &amp; Observability: Prometheus/Grafana; model drift/performance monitoring tools.&middot; DevOps: Git, GitHub/GitLab, CI/CD, testing frameworks (pytest).&middot; Cloud: Azure (preferred), AWS, GCP; serverless and managed ML services.Core Competencies &amp; Soft Skills&middot; Business acumen with the ability to prioritize use cases based on value and feasibility.&middot; Structured problem solving and hypothesis-driven experimentation.&middot; Clear written and verbal communication, storytelling with data, and visualization skills.&middot; Collaboration and mentorship across cross-functional teams (engineering, operations, compliance).&middot; Ownership mindset with a focus on reliability, safety, and continuous improvement.AI Governance, Security &amp; Compliance&middot; Adhere to corporate data governance policies, security standards, and regulatory requirements (e.g., GDPR where applicable).&middot; Implement role-based access controls, encryption, secure secrets management, and audit trails across the ML stack.&middot; Ensure models meet fairness, transparency, and explainability guidelines; conduct regular risk assessments and reviews.Success Criteria &amp; KPIs&middot; Cycle time from ideation to production (weeks).&middot; Model performance against business KPIs (e.g., accuracy, precision/recall, uplift, cost savings).&middot; Operational reliability (SLA adherence, downtime, incident rate).&middot; Adoption and user satisfaction for AI-enabled products and workflows.Compliance metrics (governance checks passed, audits completed).Job Type: Full-timePay: From QAR15,000.00 per monthEducation:<ul><li>Bachelor's (Required)</li></ul>Experience:<ul><li>AI Expert for Plant Data Model (PDM Project) : 3 years (Required)</li></ul>Language:<ul><li>Arabic (Required)</li><li>English (Required)</li></ul>License/Certification:<ul><li>degree in computer science, Data Science (Required)</li></ul>Location:<ul><li>Doha (Required)</li></ul>

AI Expert for Plant Data Model (PDM Project)

Job Overview:The Data Warehouse Expert will lead the data management, integration, governance, and operations workstreams of the Plant Data Management (PDM) project &ndash; a strategic &ldquo;Smart Plant&rdquo; initiative to create a single source of truth for all critical engineering and production data. This senior role requires a seasoned professional with at least 10 years of experience in data management in the oil &amp; gas industry. A strong background in Microsoft data warehousing technologies and an understanding of plant operational processes are essential for successKey Responsibilities:<ul><li>Evaluate the PDM project infrastructure-related components of bidder proposals, ensuring alignment architecture, data standards, &amp; operational requirements.</li><li>Lead the implementation of single source of truth, focusing on MS technologies including Azure, Microsoft 365, MSSQL, &amp; Power Platform in collaboration with implementation partners.</li><li>Collaborate with the solution enterprise architect to make sure the data warehouse design aligns with the overall solution architecture and IT infrastructure.</li><li>Lead the central repository architecture for integrated data from multiple sources (e.g. SAP, real-time systems, spreadsheets) in line with the PDM project requirements</li><li>Define the data models (schemas, tables, cubes) and storage strategy (on-premises MS SQL Server with potential hybrid cloud) to support reporting and analytics.</li><li>Ensure the configuration of ETL/ELT pipelines (using Microsoft SSIS or Azure Data Factory) to extract data from source systems, transform it, and load it into the warehouse.</li><li>Establish a robust data governance framework within the PDM scope, defining data ownership for different data domains (ensuring business stakeholders are identified as data owners), set up data stewardship roles if needed, and enforce policies for data usage, retention, and lifecycle management.</li><li>Enforce compliance with the company&rsquo;s cybersecurity and data privacy policies</li><li>Work to achieve high availability of the data platform. Implement redundancy and failover mechanisms as appropriate (clustering, backups, mirrored databases, etc.). Ensure disaster recovery plans are in place</li><li>Develop and implement data governance policies, standards, and procedures.</li><li>Collaborate with data owners and stewards to define data definitions, classifications, and quality rules.</li><li>Monitor data quality metrics and lead initiatives to resolve data issues.</li><li>Ensure compliance with data privacy regulations (e.g., GDPR, HIPAA) and internal policies.</li><li>&sect; Maintain data catalogs, metadata repositories, and data lineage documentation.</li><li>Support data governance tools and platforms, ensuring proper configuration and usage.</li><li>Conduct training and awareness programs to promote data governance best practices.</li><li>Design and implement frameworks that enable secure, self-service access to data across departments.</li><li>Promote data literacy by developing training materials and conducting workshops on data usage and governance.</li><li>Support the deployment and adoption of data catalog and self-service BI tools.</li><li>Define and manage role-based access controls to balance data accessibility with security.</li><li>Act as a liaison between IT, data teams, and business stakeholders to and ensure relevant data is discoverable and usable.</li><li>Participate in data governance councils and cross-functional working groups, to align data strategy with business goals.</li><li>Provide guidance on data stewardship responsibilities and best practices.</li></ul>Required Qualifications:Educational Background:<ul><li>Bachelor&rsquo;s degree in Information Management, Computer Science, Business, or a related field.</li><li>3+ years of experience in data governance, data management, or a related discipline.</li><li>Strong understanding of data governance frameworks.</li><li>Familiarity with data privacy laws and regulatory requirements.</li><li>Experience with data governance.</li><li>Excellent communication, collaboration, and problem-solving skills.</li><li>Ability to work independently and manage multiple priorities in a fast-paced environment.</li></ul>Expected Experience<ul><li>10+ years of experience in data management roles, including data warehouse development, system integration, and IT project management.</li><li>5+ Experience must be in the oil &amp; gas industry, dealing with industrial or enterprise data.</li></ul>Technical Skills<ul><li>Deep expertise in Microsoft Data Warehouse technologies &ndash; MS SQL Server, SQL Server Integration Services (SSIS) for ETL, SQL Server Analysis Services (SSAS) for OLAP, and SQL querying/tuning</li><li>Strong knowledge of relational and dimensional data modeling. Ability to design normalized schemas for staging and integration, as well as star/snowflake schemas for analytics.</li><li>Experience with handling large datasets (hundreds of gigabytes to terabytes) efficiently (partitioning, indexing strategies, etc.)</li><li>Hands-on experience integrating multiple systems and platforms Microsoft BizTalk, SAP, &amp; SharePoint online.</li><li>Experience implementing data governance policies and using tools for data quality and metadata management</li><li>Proficient in project management practices</li><li>Certified Data Management Professional (CDMP)</li><li>Data Governance and Stewardship Professional (DGSP)</li><li>Certified Information Privacy Professional (CIPP)</li></ul>Soft Skills:<ul><li>Excellent analytical and research skills.</li><li>Strong communication skills to collaborate with cross-functional teams.</li><li>Strong presentation skills</li></ul>Job Type: Full-timePay: From QAR15,000.00 per monthEducation:<ul><li>Bachelor's (Required)</li></ul>Experience:<ul><li>Data Warehouse : 3 years (Required)</li></ul>Language:<ul><li>Arabic (Required)</li><li>English (Required)</li></ul>License/Certification:<ul><li>degree in Information Management, Computer Science (Required)</li></ul>Location:<ul><li>Doha (Required)</li></ul>

Data Warehouse Expert

Job Profile: Cloud Infrastructure ArchitectJob Overview:The Cloud Infrastructure Architect is responsible for designing and overseeing the deployment of scalable, secure, and high-performance infrastructure to support the implementation of Plant Data Model (PDM) system. This role focuses on hybrid architecture with a strong emphasis on Microsoft technologies, including Azure, Microsoft 365, Intune, and Power Platform.The architect will evaluate infrastructure proposals submitted by implementation partners, ensure alignment with enterprise architecture and cybersecurity standards, and supervise the setup and integration of cloud and on-premises components. The role requires deep technical expertise in cloud infrastructure, virtualization, disaster recovery, and enterprise-grade networking, with proven experience in oil and gas environments.Key Responsibilities:<ul><li>Evaluate the PDM project infrastructure-related components of bidder proposals, ensuring alignment with enterprise architecture, cybersecurity standards, and operational requirements.</li><li>Lead the implementation of hybrid cloud infrastructure to support the PDM solution, with a focus on Microsoft technologies including Azure, Microsoft 365, Intune, and Power Platform in collaboration with implementation partners.</li><li>Lead the deployment and configuration of virtual machines, storage systems, networking components, and backup solutions across on-premises and cloud environments.</li><li>Ensure seamless integration of infrastructure with Active Directory, DNS, SCCM, Intune, and other enterprise services.</li><li>Oversee disaster recovery planning and high availability setup for PDM, ensuring compliance with existing DR architecture and recovery objectives.</li><li>Monitor infrastructure performance across distributed sites (e.g., Ras Laffan, Taweelah, Abu Dhabi), optimizing for latency, bandwidth, and system responsiveness.</li><li>Collaborate with system integration experts to ensure infrastructure readiness for middleware, APIs, and real-time data systems.</li><li>Enforce security protocols including encryption, role-based access controls, and secure remote access via ZTNA and MFA.</li><li>Support infrastructure scalability planning, capacity assessments, and hardware provisioning in coordination with approved vendors.</li><li>Maintain detailed documentation of infrastructure architecture, deployment plans, and operational procedures.</li><li>Provide technical oversight during implementation, testing, and go-live phases, ensuring infrastructure stability and compliance.</li></ul>Required Qualifications:Educational Background:<ul><li>A degree in computer science, Computer Engineering, information technology, or a related field</li></ul>Certifications (Preferred)<ul><li>Microsoft Certified: Azure Solutions Architect Expert</li><li>Certified Kubernetes Administrator (CKA)</li><li>TOGAF or similar enterprise architecture framework</li></ul>Expected Experience<ul><li>Minimum: 7&ndash;10 years of experience in IT infrastructure and cloud architecture</li><li>Preferred: Experience leading or supporting cloud/hybrid deployments for industrial platforms (e.g., AVEVA, Hexagon, Siemens, Bentley)</li></ul>Technical Skills<ul><li>Deep expertise in Microsoft Azure services including Virtual Machines, Azure Active Directory, Azure Storage, Azure Networking, and Azure Monitor.</li><li>Experience with Microsoft 365, Intune, and Power Platform for enterprise productivity, device management, and workflow automation.</li><li>Strong understanding of hybrid cloud architecture, including integration between on-premises infrastructure and cloud services.</li><li>Experience with Docker, Kubernetes, and Azure Kubernetes Service (AKS) for deploying and managing containerized applications in hybrid environments</li><li>Advanced knowledge of Azure Virtual Network (VNet) design, ExpressRoute, VPN gateways, DNS, load balancing, and secure network segmentation.</li></ul>Soft Skills:<ul><li>Excellent analytical and research skills.</li><li>Strong communication skills to collaborate with cross-functional teams.</li><li>Strong presentation skills</li></ul>Job Type: Full-timePay: From QAR15,000.00 per monthEducation:<ul><li>Bachelor's (Required)</li></ul>Experience:<ul><li>IT infrastructure and cloud architecture: 3 years (Required)</li></ul>Language:<ul><li>Arabic (Required)</li><li>English (Required)</li></ul>License/Certification:<ul><li>degree in computer science, Computer Engineering (Required)</li></ul>Location:<ul><li>Doha (Required)</li></ul>

Cloud Infrastructure Architect

Forvis Mazars in Qatar

<div>Job responsibilities: 
<ul><li>Responsible for overall design, operation, maintenance and continuous improvement of the data, analytics and artificial intelligence platforms used by the Security Operations Center (further referenced as SOC). Responsibilities and duties are planned as follows:</li></ul>

<ul><li>Continuous maintenance of the data pipelines, analytics platforms and AI models used by the Security Operations Center; including data ingestion, normalization, feature extraction, model training and deployment.</li></ul>

<ul><li>Ensuring the overall health of the SOC data platform, analytics engines, machine learning models, and AI-assisted detection systems.</li></ul>

<ul><li>Manage verification, validation, tuning, and quality of security telemetry including logs, NetFlow/IPFIX, EDR data, threat intelligence feeds and other SOC data sources.</li></ul>

<ul><li>Develop, train, validate and tune machine learning and analytics models used for:</li></ul>

<ul><li>Anomaly detection</li></ul>

<ul><li>Threat classification</li></ul>

<ul><li>Behavioral analysis</li></ul>

<ul><li>Alert prioritization and risk scoring</li></ul>

<ul><li>Deploy and tune detection models and analytic use cases driven by security intelligence, threat hunting and incident response requirements.</li></ul>

<ul><li>Implement analytic use cases as required by Security Intelligence, Tier-2 and Tier-3 teams.</li></ul>

<ul><li>Manage and coordinate data source onboarding, integration, normalization, enrichment and troubleshooting for all SOC telemetry sources.</li></ul>

<ul><li>Manage access and permissions for data platforms, analytics environments and AI systems used by the SOC.</li></ul>

<ul><li>Ensure that security data sources are correctly feeding the analytics and AI platforms.</li></ul>

<ul><li>Generate analytical reports, dashboards and model outputs as required by SOC management, threat hunting and incident response teams.</li></ul>

<ul><li>Configuration, management, performance tuning and capacity planning of SOC data, analytics and AI platforms.</li></ul>

<ul><li>Support proof-of-concepts (POCs) for new SOC data sources, analytics techniques and AI-driven security capabilities.</li></ul>

<ul><li>Review vendor, open-source and research developments in security analytics, machine learning and AI relevant to SOC operations.</li></ul>

<ul><li>Should have good knowledge of systems, solutions and security tools and skills as follows:</li></ul>

<ul><li>Knowledge of MS Windows and UNIX-based systems.</li></ul>

<ul><li>Knowledge of data engineering and big-data platforms (data pipelines, stream processing, data lakes).</li></ul>

<ul><li>Knowledge of security telemetry including SIEM data models, NetFlow/IPFIX, EDR telemetry and threat intelligence formats.</li></ul>

<ul><li>Knowledge of machine learning and analytics techniques including anomaly detection, classification, clustering and statistical modeling.</li></ul>

<ul><li>Knowledge of AI-driven SOC technologies including LLM-based assistants, automated enrichment and detection analytics.</li></ul>

<ul><li>Familiarity with MITRE ATT&amp;CK, incident response lifecycle and threat hunting methodologies.</li></ul>

<ul><li>Problem-solving skills to identify data quality, detection gaps and model performance issues.</li></ul>

<ul><li>Communication with SOC teams (Tier-1, Tier-2, Tier-3) to align analytics and AI capabilities with operational needs.</li></ul>

<ul><li>Communication with vendors and data providers related to SOC analytics, telemetry and AI platforms.</li></ul>

Required certifications in:

<ul><li>Data engineering, analytics or AI platforms (Cloudera, Databricks, AWS, Azure, GCP, etc.)</li></ul></div>

CSOC Data Analyst L2

Starlink Qatar

<div>
 
 The
 
 Data Governance &amp; Privacy Lead
 
 defines and drives the governance framework for data used by smart-city capabilities (including Cognitive AI). The role establishes standards for
 
 data classification, privacy-by-design, consent, retention, lineage, and controlled sharing
 
 across multi-tenant environments and multiple vendors. Working with stakeholders, security teams, and delivery vendors, the lead ensures that
 
 data products and AI pipelines comply with applicable regulations and policies
 
 , and that governance is operationalized through tooling, processes, and automated controls embedded into platform onboarding and service delivery.
 
 
 
 
 
 
 Key Responsibilities
 
 
 <ul>
 <li>
 Define
 
 data governance operating model
 
 : roles (data owners/stewards), RACI, councils, and approval workflows.
 </li>
 <li>
 Establish standards for
 
 data classification, residency, retention, legal holds, and secure disposal
 
 across tenants.
 </li>
 <li>
 Define
 
 privacy-by-design requirements
 
 : consent management, purpose limitation, minimization, and data access controls.
 </li>
 <li>
 Drive
 
 data cataloging and metadata management
 
 (ownership, descriptions, schemas, sensitivity labels, quality scores).
 </li>
 <li>
 Define
 
 lineage and provenance requirements
 
 for data pipelines and AI artifacts (datasets, labels, embeddings, vector indexes).
 </li>
 <li>
 Specify
 
 DLP and egress control requirements
 
 for storage, APIs, and AI/RAG workflows; coordinate with Cybersecurity Architect.
 </li>
 <li>
 Define
 
 data-sharing policies and contracts
 
 (inter-agency sharing, vendor access boundaries, anonymization/masking rules).
 </li>
 <li>
 Establish
 
 data quality framework
 
 : validations, monitoring, SLA/KPIs, issue management, and remediation processes.
 </li>
 <li>
 Provide
 
 governance assurance for vendor deliverables
 
 (design reviews, acceptance criteria, compliance evidence packs).
 </li>
 <li>
 Enable
 
 operations
 
 : governance dashboards, audit reporting, periodic access reviews, and training for data owners/stewards.
 </li>
 </ul>
 
 
 
 
 
 Skills &amp; Abilities
 
 
 <ul>
 <li>
 Strong knowledge of
 
 data governance, privacy, and compliance practices
 
 in regulated environments.
 </li>
 <li>
 Ability to
 
 operationalize governance
 
 through processes and automated technical controls (policy-as-code mindset).
 </li>
 <li>
 Understanding of
 
 modern data platforms
 
 (lakehouse, streaming, catalog/lineage) and
 
 AI data lifecycle
 
 (RAG/embeddings).
 </li>
 <li>
 Excellent
 
 stakeholder management
 
 across legal, security, business owners, and vendor teams.
 </li>
 <li>
 Strong
 
 documentation, control definition, and audit-readiness skills
 
 .
 </li>
 </ul>
 
 
 
 
 
 Education &amp; Experience
 
 
 <ul>
 <li>
 Bachelor&rsquo;s degree in
 
 Computer Science, Information Technology, Cybersecurity
 
 ; Master&rsquo;s degree highly preferred.
 </li>
 <li>
 
 7+ years
 
 in data governance, privacy, compliance, or data management roles (government/telco preferred).
 </li>
 <li>
 Experience implementing
 
 data catalog/lineage tools
 
 and defining enterprise-wide data standards and policies.
 </li>
 <li>
 Experience with
 
 privacy controls
 
 (consent, RTBF/DSR processes, anonymization/masking, retention schedules).
 </li>
 <li>
 Background working with
 
 delivery vendors
 
 and integrating governance into program delivery and acceptance gates.
 </li>
 <li>
 Familiarity with
 
 AI data governance concepts
 
 (dataset/model cards, provenance, RAG content governance).
 </li>
 </ul>
 
 
 
 
 
 Preferred Tools
 
 
 <ul>
 <li>
 
 Data governance/catalog:
 
 Microsoft Purview (or equivalent), data classification/labeling tools
 </li>
 <li>
 
 Data protection:
 
 DLP tooling, encryption/CMK/HSM, key management (Key Vault/KMS)
 </li>
 <li>
 
 Data platforms:
 
 lakehouse (Delta/Iceberg), streaming (Kafka/Event Hubs), SQL/ETL orchestration (Airflow)
 </li>
 </ul>
 
 
 
 
 
 Soft Skills
 
 
 <ul>
 <li>
 Strong
 
 facilitation and consensus-building
 
 (data councils, policy workshops)
 </li>
 <li>
 Ability to
 
 translate legal/privacy requirements into actionable technical controls
 
 </li>
 <li>
 High
 
 attention to detail
 
 with pragmatic prioritization
 </li>
 <li>
 Confidence to
 
 challenge non-compliant designs
 
 and drive remediation
 </li>
 <li>
 Effective
 
 communication and training approach
 
 for non-technical stakeholders
 </li>
 </ul>
</div>

Data Governance & Privacy Lead

Mindstream

Role: Civil Engineer- Oil and Gas experience is must in GCCLocation: Ras LaffanDuration: 6 months and extendableSalary: Based on meritExperience :10 YearsEducation: BachelorsMore than 10 years of engineering experience in Plant Project. (Preferred Oil and Gas project experience)<ul><li>Working knowledge of codes and standards relative to civil engineering.</li></ul><ul><li>Field Engineer experience of more than 2 projects in LNG/Gas plant</li></ul><ul><li>Project execution experience in middle east country</li></ul>Job Type: ContractApplication Question(s):<ul><li>What is your current and expected salary? Notice period?</li><li>How many years do you have experience in the Oil &amp; Gas industry?</li><li>Are you willing to work under MS payroll for a 6-month extendable contract?</li><li>Are you available to join immediately?</li><li>Do you have freelancing visa?</li></ul>

CIVIL ENGINEER - Oil & Gas

Scale AI

<div>
 Role Overview
 
 
 Scale&rsquo;s rapidly growing Global Public Sector team is focused on using AI to address critical challenges facing the public sector around the world. Our core work consists of:
 
 
 <ul>
 <li>
 Creating custom AI applications that will impact millions of citizens
 </li>
 <li>
 Generating high-quality training data for national LLMs
 </li>
 <li>
 Upskilling and advisory services to spread the impact of AI
 
 
 </li>
 </ul>
 As a Production AI Ops Lead, you will design and develop the production lifecycle of full-stack AI applications, while supporting end-to-end system reliability, real-time inference observability, sovereign data orchestration, high-security software integration, and the resilient cloud infrastructure required for our international government partners.
 
 
 At Scale, we&rsquo;re not just building AI solutions&mdash;we&rsquo;re enabling the public sector to transform their operations and better serve citizens through cutting-edge technology. If you&rsquo;re ready to shape the future of AI in the public sector and be a founding member of our team, we&rsquo;d love to hear from you.
 
 
 
 You will:
 
 
 
 <ul>
 <li>
 Own the production outcome: Take full accountability for the long-term performance and reliability of AI use cases deployed across international government agencies.
 </li>
 <li>
 Ensure Full-Stack integrity: Oversee the end-to-end health of the platform, ensuring seamless integration between the AI core and all full-stack components, from APIs to UI, to maintain a responsive and production-ready environment.
 </li>
 <li>
 Scale the feedback loop: Build automated systems to monitor model performance and data drift across geographically dispersed environments, ensuring the right levels of reliability.
 </li>
 <li>
 Navigate global compliance: Manage the technical lifecycle within diverse regulatory frameworks.
 </li>
 <li>
 Incident command: Lead the response for production issues in mission-critical environments, ensuring rapid resolution and building the guardrails to prevent them from happening again.
 </li>
 <li>
 Bridge the gap: Translate deep technical performance metrics into clear insights for senior international government officials.
 </li>
 <li>
 Drive product evolution: Partner with our Engineering and ML teams to ensure the lessons learned in the field directly influence the technical architecture and decisions of future use cases.
 
 
 </li>
 </ul>
 
 Ideally, you have:
 
 
 
 <ul>
 <li>
 Experience: 6+ years in a high-impact technical role (SRE, FDE or MLOps) with experience in the public sector.
 </li>
 <li>
 Global perspective: Familiarity with international government security standards and the complexities of deploying sovereign AI.
 </li>
 <li>
 System architecture proficiency: Proven experience maintaining production-grade applications with a deep understanding of the full request lifecycle-connecting frontend/API layers to the backend and AI core.
 </li>
 <li>
 Modern AI Stack expertise: Proficiency in coding and the modern AI infrastructure, including Kubernetes, vector databases, agentic development, and LLM observability tools.
 </li>
 <li>
 Ownership: You treat every production deployment as your own. You race toward solving hard problems before the customer even sees them.
 </li>
 <li>
 Reliability: You understand that in the public sector, a model failure may be a risk to public safety or privacy.
 </li>
 <li>
 Customer communication: The ability to explain to a high-ranking official why the performance of the system has degraded and how we are fixing it.
 
 
 </li>
 </ul>
 
 
 PLEASE NOTE:
 
 
 
 Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants.
 
 
 
 
 About Us:
 
 
 
 
 At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Cisco, DLA Piper, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications.
 
 
 
 
 We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status.
 
 
 
 
 We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at accommodations@scale.com. Please see the United States Department of Labor's
 
 
 Know Your Rights poster
 
 
 for additional information.
 
 
 
 
 We comply with the United States Department of Labor's
 
 
 Pay Transparency provision
 
 
 .
 
 
 
 
 
 PLEASE NOTE:
 
 We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants&rsquo; needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our privacy policy for additional information.
 
</div>

AI Applications Ops Lead, GPS

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