Location: EMEA (CET) We are looking for a Senior AI Enablement & Implementation Specialist to deliver AI-enabled workflows across internal teams. This role focuses on translating business needs into structured AI use cases, coordinating cross-functional implementation, and ensuring adoption through documentation, training, and governance. You will own the lifecycle of AI initiatives, maintain a centralized AI knowledge base, and ensure solutions are reliable, reusable, and easy to use for both technical and non-technical teams. WHAT YOU'LL DO: - Translate real business problems into clear AI requirements, prompts, and workflows. - Design context and evaluation frameworks so AI outputs are reliable, measurable, and reusable. - Lead AI-enabled projects involving summarization, generation, classification, or decision support. - Participate in the development of the AI knowledge base and use case repository. - Support the development of training materials and educational resources, including the evaluation and refinement of technical content. - Scout new AI tools and models, run quick POCs, and assess their value before wider adoption. - Contribute to AI communication channels, AI implementation culture events, and participate in AI- and automation-related activities. - At least 2 years of proven experience leading AI, automation, or other innovation-focused initiatives within an organization. - Analytical mindset with the ability to identify system issues and unblock teams. - Strong facilitation and communication skills — able to tailor discussions for both technical and non-technical audiences. - Familiarity with large language models, creative AI tools, and API-based workflows. - Clear, thoughtful communicator — able to write documentation and instructions that people actually use and understand. - Located in the EMEA region, working CET hours. NICE TO HAVE: - Hands-on experience with prompt engineering, Python, or SQL. - Engineering background. - Certifications in project management methodologies. - Experience in AdTech, MarTech, or client support. WHAT WE OFFER: - USD compensation that values your expertise.‍ - Work from anywhere: Fully remote to suit your lifestyle.‍ - 31 days of paid time off: 21 days of annual leave + 10 days of sick leave, because your health and work-life balance matter.‍ - Growth-focused environment: Access to learning resources and clear pathways for growth.‍ - Fun team events: Virtual cooking classes, yoga sessions, team quizzes and more - ‍A culture of trust: We cut the red tape — results over rules always. Open talk, ownership, and getting things done together.

Job Title: AI/ML Engineer Location: Dayton, OH and Remote Employment Type: Full-Time Clearance requirements: TS/SCI About the Role Rackner is seeking a highly skilled AI/ML Engineer to design, develop, and deploy advanced machine learning solutions that support mission-critical systems. This role will focus on building scalable models, developing training pipelines, and collaborating with cross-functional teams to deliver impactful AI-driven solutions. Key Responsibilities - Design, develop, and implement machine learning and deep learning models - Build and optimize model architectures including CNNs, RNNs, and transformer-based models - Develop and deploy Large Language Models (LLMs) and object detection systems (e.g., YOLO, Faster R-CNN) - Perform feature engineering and prepare high-quality datasets for training and evaluation - Create and maintain AI/ML training runbooks and documentation - Collaborate with data engineers and software teams to integrate models into production systems - Ensure reproducibility through data versioning and metadata standards - Continuously evaluate and improve model performance and scalability Required Qualifications - Strong proficiency in designing and implementing model architectures, including: - Convolutional Neural Networks (CNNs) - Recurrent Neural Networks (RNNs) - Transformer-based architectures - Large Language Models (LLMs) - Object Detection models (e.g., YOLO, Faster R-CNN) - Hands-on experience with: - PyTorch and/or TensorFlow - Hugging Face, Ollama, or similar frameworks - Experience with data engineering concepts, including: - Feature engineering and dataset preparation - Data versioning tools (e.g., lakeFS) - Metadata standards such as STAC - Ability to create clear and effective AI/ML training runbooks - Strong problem-solving skills and ability to work in a collaborative environment Preferred Qualifications - Experience deploying models in cloud-native environments - Familiarity with DevSecOps practices - Experience working with large-scale or federal datasets - Understanding of MLOps principles and pipelines Benefits & Perks - Weekly pay with full remote flexibility - Professional growth investment, including paid certifications and training - Comprehensive benefits package, including: - Medical, dental, and vision coverage - 401(k) with 100% company match up to 6% - Paid time off (PTO) - Life and disability insurance - Home office equipment plan - A supportive, inclusive team culture focused on collaboration, trust, and mission impact About Rackner Rackner is a cloud-native software consultancy delivering solutions for startups, enterprises, and the public sector. We enable digital transformation through DevSecOps, AI/ML, and cloud-first innovation. Our teams solve high-impact problems that advance federal missions and strengthen national readiness. Join us to help shape the future of secure, scalable data systems supporting mission success.

Role Description The Senior Principal Product Enablement Specialist, AI will serve as a senior technical enablement expert responsible for enabling AI-powered platform capabilities across the Simulations Plus ecosystem. This role focuses on the enablement, implementation, and operational readiness of AI agents, AI-assisted workflows, and the composition layer that supports cross-product functionality. This individual contributor role provides the opportunity to shape how AI capabilities are delivered and adopted across products while remaining hands-on with implementation, testing, and customer enablement. Job Responsibilities - AI Product Enablement Leadership - Define and establish enablement best practices for AI-powered capabilities across the ecosystem - AI composition layer integration - Shared AI agents (e.g., data agents, reporting agents) - Cross-product AI workflows - Develop implementation frameworks for deploying AI capabilities consistently across products - Establish standards for AI feature testing, validation, and operational readiness - Create reusable implementation patterns and configuration templates for AI capabilities - Drive standardization of AI documentation, enablement materials, and training resources - AI Capability Implementation - Implement AI agents and AI-assisted features within product workflows - Integrate AI agents with product APIs and services - Configure AI pipelines and execution environments - Adapt shared AI capabilities to product-specific contexts - Collaborate with engineering and product teams to operationalize AI features - Support integration of shared AI services into multiple product environments - Identify and resolve implementation challenges during development and deployment - Ensure AI features function consistently across the product ecosystem - AI Feature Testing and Validation - Develop and execute testing frameworks for AI-powered product capabilities - Functional testing of AI agents - Evaluation pipelines for AI outputs - Reliability and performance testing - Implement human-in-the-loop validation strategies for AI-assisted workflows - Identify edge cases and failure modes in AI-driven features - Work with engineering teams to improve reliability and monitoring of AI systems - Establish quality assurance practices specific to AI-enabled product features - Documentation and Training - Develop comprehensive documentation for AI-enabled product capabilities - Architecture and usage documentation - Implementation and integration guides - Troubleshooting resources - Create training curricula for internal teams and customers adopting AI capabilities - Produce educational materials explaining AI workflows and agent capabilities - Ensure documentation remains aligned with evolving AI platform capabilities - Support onboarding and training of teams implementing AI-powered workflows - Operational Support and Troubleshooting - Serve as a technical escalation point for complex AI feature deployments - Diagnose and resolve issues related to AI agents, pipelines, and workflows - Support services and support teams in troubleshooting AI-enabled functionality - Identify patterns in operational issues to improve AI reliability and usability - Contribute improvements to operational practices for AI-powered features - Cross-Product Collaboration - Collaborate with Product and Engineering teams to ensure consistent AI capability delivery - Work with Services and Support teams to capture operational insights from AI deployments - Provide feedback to product teams on usability and adoption challenges - Identify opportunities to reuse AI capabilities across products and workflows - Help maintain alignment between AI platform capabilities and product-level implementations Qualifications - 7+ years of experience working with AI-enabled software products or AI platforms - Experience implementing LLM-based systems, AI agents, or AI pipelines - Experience with evaluation frameworks for AI outputs - Strong understanding of AI reliability, monitoring, and operational practices - Ability to translate AI capabilities into practical product functionality - Experience implementing complex software systems or platform capabilities - Working with APIs and distributed services - Strong programming or scripting experience (Python or similar languages commonly used in AI development) - Experience working with modern AI tooling and development frameworks - Demonstrated ability to support multiple product environments simultaneously - Strong technical communication and documentation skills - Ability to collaborate effectively with product, engineering, and operations teams - Strong organizational skills and ability to manage multiple initiatives Preferred Qualifications - Experience working with AI agent architectures and orchestration frameworks - Experience implementing retrieval-augmented generation or knowledge-based AI systems - Familiarity with AI evaluation pipelines and observability tooling - Experience deploying AI capabilities in enterprise software environments - Familiarity with cloud-based AI infrastructure and deployment models - Experience supporting cross-product platforms or shared services - Understanding of API-based product architectures Education - Bachelor’s degree in computer science, data science, artificial intelligence, or related field - Masters or PhD in computer science, data science, artificial intelligence, or related field preferred

• Build AI-Powered Features: Design, develop, and deploy production-grade AI applications that solve real customer problems, from concept to deployment • Architect Scalable Systems: Create robust backend architectures that support AI workloads, ensuring low latency, high reliability, and seamless integration with existing services • Drive AI Innovation: Implement and optimize agentic AI systems, RAG pipelines, and multi-agent workflows using modern LLM frameworks • Own the Full Stack: Take end-to-end ownership of features, from database design and API development to AI model integration and monitoring • Collaborate Cross-Functionally: Work closely with product, design, and data teams to translate business requirements into technical solutions • Optimize and Iterate: Run experiments, A/B tests, and evaluations to continuously improve AI system performance and user experience