Santex is a US-based global company founded in 1999, with 26 years of experience in the software industry. Headquartered in California with offices in Córdoba, Argentina, its talent network spans over 18 countries thanks to its flexible, remote-first culture. Santex specializes in custom enterprise software development, operating through Hubs that include eCommerce, BIM, Mobility, Content Delivery, Integration, Web & Mobile Development, Cloud Computing, Artificial Intelligence (AI), Data Science, IT Consulting, and Services. The company is committed to making a positive impact across three dimensions: economic, social, and environmental. Job Description: We are seeking an AI Enablement Engineer to design and scale the semantic layer that turns raw restaurant data into a shared language for AI, analytics, and decision-making across a global Quick Service Restaurant (QSR) enterprise. This is a foundational role in our AI strategy: the semantic layer you build is what makes natural language analytics, automated reporting, and intelligent AI agents possible at enterprise scale. Your focus is bridging business meaning and data, ensuring that AI systems, analytics platforms, and end users consistently interpret critical metrics like same-store sales, speed of service, traffic, and labor productivity in a standardized, governed way. When an AI agent or a franchisee asks "how did my restaurant perform last week," the accuracy and trust of that answer starts with your work. You will define and operationalize a hybrid semantic layer strategy that combines governed, metadata-driven models with AI-powered context engineering to enable scalable, accurate, and self-service insights across restaurants, corporate teams, and franchisees, unlocking the building blocks for conversational analytics and autonomous AI workflows. Key Responsibilities – Semantic Layer Strategy & Architecture - Define and implement an enterprise semantic layer that standardizes metric definitions and aligns business questions to data - Establish canonical definitions for core KPIs (e.g., same-store sales, speed of service, traffic, labor productivity) - Design mapping between business concepts and underlying data models across systems (POS, digital, supply chain, finance) - Provide structured metadata to power AI systems, copilots, and analytics tools. Key Responsibilities – Hybrid Semantic Model Implementation - Build and maintain manual, metadata-driven semantic models for high-criticality domains (finance, core KPIs, franchise reporting) - Enable AI-driven context engineering for exploratory analytics, operational insights, and ad-hoc queries - Define how both approaches coexist in a unified architecture Key Responsibilities – Tooling & Platform Enablement - Implement semantic layer tooling (DBT, semantic views, YAML/Markdown metadata, data catalogs like Atlan) - Enable downstream consumption by BI tools, APIs, and AI applications - Create reusable abstractions and templates to scale globally Key Responsibilities – AI & Context Engineering Integration - Enable AI systems (LLMs, agents, copilots) to leverage semantic metadata - Support context engineering using data lineage, metadata, example queries, and repository context - Improve AI reliability by grounding outputs in governed definitions Key Responsibilities – Governance & Data Quality - Establish governance processes for metric definitions - Ensure alignment across regions, brands, and franchise reporting - Implement validation, versioning, and change management - Define guardrails to prevent inaccurate analytics outputs Key Responsibilities – Adoption & Enablement - Partner with business and technical teams to drive adoption - Educate stakeholders on standardized metrics and self-service analytics - Provide documentation, playbooks, and training Required Qualifications - Bachelor’s or Master’s degree in Computer Science, Data Engineering, Analytics, or related field - 5+ years of experience in data engineering, analytics engineering, or AI/ML systems - Strong experience with semantic modeling or analytics engineering - Proficiency in SQL and Python - Experience with DBT and modern cloud data platforms - Understanding of APIs and distributed systems Preferred Qualifications - Experience in QSR, retail, or franchise environments - Experience with semantic/metrics layers - Familiarity with data catalogs (e.g., Atlan) - Experience with generative AI, LLMs, and context engineering - Knowledge of data lineage and governance frameworks Additional Expectations - Design and maintain CI/CD pipelines, including automated builds, testing, and deployment of solutions - Develop and execute functional and regression test suites to validate metric accuracy, data completeness, and semantic model behavior across environments - Implement automated data and code quality checks and integration tests within the deployment pipeline to catch issues before they reach production - Apply software engineering best practices including version control, code review, branching strategies, and environment promotion (dev/staging/prod) to all semantic layer and metadata assets - Monitor platform performance, troubleshoot pipeline failures, and maintain observability across semantic layer infrastructure using logging, alerting, and health checks - Define and manage infrastructure as code (e.g., Terraform, CloudFormation) for data platform resources, ensuring reproducible and auditable environment provisioning across development, staging, and production - Implement and maintain role-based access controls, secrets management, and security policies across semantic layer tooling, data platform resources, and API integrations to ensure compliance with enterprise security standards Key Skills & Competencies - Systems thinking across data, analytics, and AI - Ability to translate business metrics into data models - Balance governance with scalability - Strong stakeholder management - Clear communication of complex concepts Success Metrics - Adoption of standardized metric definitions - Reduction in reporting inconsistencies - Improved accuracy of AI-generated insights - Increased self-service analytics usage - Faster time-to-insight Reporting Structure - Reports to: VP / Director of Data, AI, or Platform Engineering - Works closely with: Data Engineering, Analytics, AI/ML, Finance, Operations, Franchise teams Summary The AI Enablement Engineer (Semantic Layer) establishes a shared language between business and data. By combining governed semantic models with AI-driven context understanding, this role enables scalable, accurate, and trusted analytics and AI across a global QSR enterprise. Location: LATAM

Tenstorrent is leading the industry on cutting-edge AI technology, revolutionizing performance expectations, ease of use, and cost efficiency. With AI redefining the computing paradigm, solutions must evolve to unify innovations in software models, compilers, platforms, networking, and semiconductors. Our diverse team of technologists have developed a high performance RISC-V CPU from scratch, and share a passion for AI and a deep desire to build the best AI platform possible. We value collaboration, curiosity, and a commitment to solving hard problems. We are growing our team and looking for contributors of all seniorities. Tenstorrent is seeking an AI Performance Simulation Architect to help shape the future of our AI computing. In this role, you’ll architect and build scalable cycle-accurate AI accelerator performance models that can run representative AI workloads. Your work will directly inform how we design and optimize future hardware platforms, from high-level performance models to cycle-accurate simulations. This role is remote, based out of North America. We welcome candidates at various experience levels for this role. During the interview process, candidates will be assessed for the appropriate level, and offers will align with that level, which may differ from the one in this posting. Who You Are - You’re a senior technical leader with deep experience in AI accelerator architecture and micro-architecture, performance simulation, and system-level modeling. - You’re comfortable switching between abstraction layers—from C++ performance models to software frameworks and system requirements. - You have a strong grasp of AI workloads and how to distill them into inputs for performance models. - You understand how system design affects the performance and scalability of AI workloads. - You collaborate well across hardware, software, and research domains—and enjoy mentoring others along the way. What We Need - Architect and develop simulation environments for AI systems—spanning accelerators, NoCs, and memory hierarchies. - Define and implement abstraction layers, from high-level analytical models to detailed simulations using tools like GEM5 or SST. - Lead performance modeling and bottleneck analysis to guide architectural design and system optimization. - Lead integration of the AI accelerator performance model into a larger heterogeneous simulation modeling environment to examine system performance. - Deep experience with parallel programming (OpenMP, MPI, CUDA, OpenCL) and system analysis tools. What You Will Learn - How Tenstorrent is building next-gen AI infrastructure at datacenter scale. - How to influence silicon and system-level decisions using simulation-driven insights. - How to collaborate with vendors and technology partners to assess emerging processors, accelerators, and interconnects. - How to bridge simulation and deployment by working across hardware, dev tools, software stacks, and customer use cases. Compensation for all engineers at Tenstorrent ranges from $100k - $500k including base and variable compensation targets. Experience, skills, education, background and location all impact the actual offer made. Tenstorrent offers a highly competitive compensation package and benefits, and we are an equal opportunity employer. This offer of employment is contingent upon the applicant being eligible to access U.S. export-controlled technology. Due to U.S. export laws, including those codified in the U.S. Export Administration Regulations (EAR), the Company is required to ensure compliance with these laws when transferring technology to nationals of certain countries (such as EAR Country Groups D:1, E1, and E2). These requirements apply to persons located in the U.S. and all countries outside the U.S. As the position offered will have direct and/or indirect access to information, systems, or technologies subject to these laws, the offer may be contingent upon your citizenship/permanent residency status or ability to obtain prior license approval from the U.S. Commerce Department or applicable federal agency. If employment is not possible due to U.S. export laws, any offer of employment will be rescinded.

AI Technology Usability Researcher (contract) Location: Remote in Seattle, WA area only Pay: $55-$60 Hourly DOE Job Description: Ready to advance your career with a Fortune 100 Technology Industry Leader? Our client is seeking an AI Technology Usability Researcher to join a group of research peers as they evaluate and improve the user experience for their well-known internal products. The AI Technology Usability Researcher must be able to communicate clearly cross-functionally, work in a fast paced environment, and make clear strong decisions. The researcher will partner with external research vendors to help screen and recruit participants for studies, and will run rapid research across both short‑term and expanded portfolio projects. This role will also help build, set up, and manage a pipeline of UX research, ensuring studies are executed efficiently and at scale. If this sounds like you, please read along and apply! RESPONSIBILITIES - Research Execution and Project Management: Execute multiple concurrent research projects as assigned to evaluate task performance of Excel and Copilot compared with competitors - Generative and Evaluative Research: Conduct quick-turnaround qualitative and mixed-methods research to generate insights for Excel and Copilot. - Data Analysis and Synthesis: Analyze and synthesize diverse data sources, prioritize findings, and clearly summarize work in visually well-designed, clear and actionable reports. - Project Management: Coordinate with multiple research and product team partners, study recruitment vendors/panel management, and research ops to move projects forward. - Hands-on Research Execution: study design, benchmark execution, analysis, etc. - Rapid Insight Generation: Execute research and compile insights quickly to maximize impact. - Rapid Output Generation: Creating assets such as videos, presentations, and documents to summarize the insights. SKILLS & EXPERIENCE (REQUIRED) - An advanced degree in Engineering, Social Science, or other data or research-centric field. - Proven experience in designing and executing mixed-methods UX research, including observing, understanding, and synthesizing human behavior into insights, to drive customer-focused product development. - Exceptional project management, organizing, and planning skills with keen attention to detail. - Strong written and verbal communication skills, with the ability to present and influence data-driven decisions. - Proficiency in qualitative research methods, insight synthesis, and generating insightful reports/outputs. - 6 months+ experience researching generative AI / LLM in a professional setting A passion for translating ideas, needs, and requests into rigorous and valid research questions. SKILLS & EXPERIENCE (DESIRABLE) - An advanced degree in Human Computer Interaction, Human Factors, or related fields. - Experience conducting user research on AI, particularly generative AI (LLMs) EEO Employer Apex Systems is an equal opportunity employer. We do not discriminate or allow discrimination on the basis of race, color, religion, creed, sex (including pregnancy, childbirth, breastfeeding, or related medical conditions), age, sexual orientation, gender identity, national origin, ancestry, citizenship, genetic information, registered domestic partner status, marital status, disability, status as a crime victim, protected veteran status, political affiliation, union membership, or any other characteristic protected by law. Apex will consider qualified applicants with criminal histories in a manner consistent with the requirements of applicable law. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation in using our website for a search or application, please contact our Employee Services Department at 844-463-6178. Apex Systems is a world-class IT services company that serves thousands of clients across the globe. When you join Apex, you become part of a team that values innovation, collaboration, and continuous learning. We offer quality career resources, training, certifications, development opportunities, and a comprehensive benefits package. Our commitment to excellence is reflected in many awards, including ClearlyRated's Best of Staffing in Talent Satisfaction in the United States and Great Place to Work in the United Kingdom and Mexico. Apex uses a virtual recruiter as part of the application process. Apex Benefits Overview: Apex offers a range of supplemental benefits, including medical, dental, vision, life, disability, and other insurance plans that offer an optional layer of financial protection. We offer an ESPP (employee stock purchase program) and a 401K program which allows you to contribute typically within 30 days of starting, with a company match after 12 months of tenure. Apex also offers a HSA (Health Savings Account on the HDHP plan), a SupportLinc Employee Assistance Program (EAP) with up to 8 free counseling sessions, a corporate discount savings program and other discounts. In terms of professional development, Apex hosts an on-demand training program, provides access to certification prep and a library of technical and leadership courses/books/seminars once you have 6+ months of tenure, and certification discounts and other perks to associations that include CompTIA and IIBA. Apex has a dedicated customer service team for our Consultants that can address questions around benefits and other resources, as well as a certified Career Coach. You can access a full list of our benefits, programs, support teams and resources within our 'Welcome Packet' as well, which an Apex team member can provide.

Job Quick Facts: • Specialty: Teleradiology • Job Type: Locum Tenens • Facility Location: VA • Service Setting: Inpatient/Outpatient • Reason For Coverage: Supplemental • Coverage Period: ASAP - Ongoing • Coverage Type: Call only • Call Schedule: 24-hr call; 24/7 • Support Staff: Available • Duties: - Interpret and dictate diagnostic imaging studies via DICOM - STAT reads within 45 minutes; Stroke Protocol CTs within 30 minutes - Routine reads within 24 hours - Communicate critical findings directly to ordering physician - Participate in peer review and QA processes - Will service VISN 9 Medical Centers & their associated radiology service locations • Other Info: - PACS Dictation System - Full teleradiology platform - Secure connectivity to VA systems (PACS, VistA) - HL7 interface for reports - Web-based portal for exam management - Voice recognition /dictation system • Malpractice insurance covered Requirements: • Active & unrestricted license in any state • BC/BE in Diagnostic Rad and or Nuclear Med • DEA • HIPAA & VA mandatory training compliance • Certificate of completion for privacy & security & patient privacy HIPPA training courses