Your Mission This is a company built for growth. At exmox, you'll work on real systems at scale. We build high-performing consumer products used by millions in a highly competitive, global mobile gaming ecosystem powered by event-driven architectures, complex business logic, and fast feedback loops. We're scaling fast around one of the most exciting innovations in mobile gaming: a rewarded user engagement and acquisition platform that helps publishers acquire and retain players. That means distributed systems, evolving architectures, and problems that don't have textbook answers. We are looking for an Applied AI Engineer (f/m/x) to design, build, and ship production-grade systems that weave large language models, agentic workflows, and generative AI tools into the core of our product and business operations. You will own the full lifecycle from prototyping an AI-powered automation to hardening it for production on AWS working in Python and FastAPI on a modern cloud-native stack. This is not a research role. You will spend your time writing backend services, designing robust integrations with third-party AI APIs, and building agentic pipelines that replace manual business processes with intelligent, self-improving workflows. If you're excited by complex systems, high traffic, and applied AI at scale, we want to hear from you. What You’ll Own - Backend development: Design and build performant, well-tested Python/FastAPI services that power AI-driven features and automations. - Agentic workflow design: Architect multi-step AI agent pipelines using frameworks such as LangGraph, CrewAI, or custom orchestration layers. Define tool schemas, manage state, implement retry/fallback logic, and ensure human-in-the-loop controls where required. - LLM integration: Integrate LLM providers (OpenAI, Anthropic, open-source models) via APIs and SDKs. Manage prompt engineering, context-window strategies, structured output parsing, streaming, caching, and cost optimization. - Generative media API integration: Connect and orchestrate external AI creative tools such as Arcads, Seedance, Runway and more into automated content pipelines. - Business process automation: Identify, propose, and implement AI-native automations across the organization from content creation workflows to data enrichment, QA, customer support, and internal tooling. - Cloud & DevOps: Collaborate closely with our Platform team to deploy and operate services on AWS. Manage observability, and cost governance for AI workloads. - Collaboration: Work closely with product, design, and business stakeholders to translate ambiguous business needs into concrete AI-powered solutions. What You Bring - Backend engineering: 5+ years of production Python experience, with strong hands-on knowledge of FastAPI or similar frameworks - LLM integration: Proven experience building LLM-powered applications including prompt engineering, context management, structured outputs, and cost optimization across providers like OpenAI or Anthropic - Agentic systems: Hands-on experience designing multi-step agent pipelines using frameworks such as LangGraph, CrewAI, or custom orchestration layers, including state management, tool schemas, and fallback logic - API integrations: Experience integrating third-party APIs at scale, ideally including generative media or creative AI tools - Engineering mindset: You write clean, tested, production-ready code and take full ownership of what you ship - Stakeholder collaboration: Able to translate ambiguous business problems into concrete technical solutions, working closely with non-technical stakeholders Nice to have: - Generative media: Exposure to video, image, or audio generation APIs such as Runway, Seedance, or similar - Human-in-the-loop: Experience with AI quality assurance or approval workflows - Scale-up experience: Background in fast-paced, product-led environments What You Can Expect - Ambitious people, real ownership. Work with driven people who challenge each other openly and take full ownership of meaningful parts of the business. - A company that prioritizes growth, performance, and impact. Comfort isn’t the goal here, progress is. We set a high bar and focus on delivering real results. - A highly ambitious environment with a clear goal. Building the next European tech challenger is not just an idea, it is our mission. Everything we do is driven by the ambition to compete at the highest level and win. - Direct exposure to leadership and real decision-making. You’ll work closely with experienced leaders, contribute to strategic discussions, and see how decisions shape the business in real time.

Company Description It all started in sunny San Diego, California in 2004 when a visionary engineer, Fred Luddy, saw the potential to transform how we work. Fast forward to today — ServiceNow stands as a global market leader, bringing innovative AI-enhanced technology to over 8,100 customers, including 85% of the Fortune 500®. Our intelligent cloud-based platform seamlessly connects people, systems, and processes to empower organizations to find smarter, faster, and better ways to work. But this is just the beginning of our journey. Join us as we pursue our purpose to make the world work better for everyone. Job Description ROLE DESCRIPTION As a Sr. Delivery Acceleration AI Engineer, you will design, develop, and optimize AI-powered autonomous implementation solutions that transform how ServiceNow Expert Services deliver customer implementations. Working within the Delivery Acceleration team, you’ll focus on building and refining AI agents that automate ServiceNow configuration, generate implementation artifacts, and accelerate time-to-deploy—turning what previously required weeks of manual effort into AI-driven delivery that produces production-ready outputs in hours. This role requires deep expertise in prompt engineering, AI agent architecture, and an understanding of enterprise professional services delivery. You’ll work directly with autonomous implementation platforms built on large language models to create, test, and refine the AI-driven workflows that generate ServiceNow configurations, user stories, test scripts, and deployment packages for customer engagements. Critically, you must understand the professional services go-to-market motion—how services are scoped, sold, estimated, and delivered—because the AI solutions you build must align with how consultants and sales teams position and execute customer engagements. Your work directly impacts delivery speed, quality, margin, and the customer experience. Success requires balancing technical depth in AI/LLM systems with practical business acumen. You’ll operate in a fast-paced sprint cadence where AI capabilities evolve rapidly, requiring continuous experimentation, rigorous quality validation, and close collaboration with solution architects, product managers, and delivery consultants across AMS, EMEA, and APAC+JPN. You will partner closely with the platform administrator who owns operations, adoption, and governance for the AI-powered deal and delivery document generator, ensuring the AI agents and prompt assets you build are deployed, scaled, and governed effectively across the global delivery community. WHAT YOU GET TO DO IN THIS ROLE: Design & Develop AI-Powered Implementation Agents - Architect and build AI agent workflows that autonomously generate ServiceNow configurations, implementation plans, user stories, and test scripts from customer requirements - Develop, test, and iterate sophisticated prompt chains and orchestration patterns that produce consistent, production-quality outputs across ServiceNow product workflows (ITSM, CSM, HRSD, SPM, etc.) - Design multi-step agentic processes that handle complex implementation logic—scope validation, dependency mapping, configuration generation, and quality assurance—with minimal human intervention - Build and maintain prompt libraries, templates, and reusable patterns that encode delivery best practices and Gold Implementation standards into AI agent behavior, partnering with the platform administrator on library structure, versioning, and publication to end users - Partner with AI Architects and Solution Architects to ensure agent outputs align with ServiceNow platform strategy, product direction, and enterprise readiness standards Lead Prompt Engineering & AI Quality Optimization - Serve as a subject matter expert in prompt engineering techniques for large language models, including chain-of-thought reasoning, few-shot learning, structured output generation, and context window optimization - Design and execute systematic prompt evaluation frameworks that measure output accuracy, consistency, completeness, and adherence to ServiceNow implementation standards - Continuously optimize prompt performance through A/B testing, output analysis, and iterative refinement—treating prompts as production code with version control and quality gates, incorporating user feedback and quality-audit signals surfaced by the platform administrator and the champions network - Develop guardrails and validation logic that ensure AI-generated configurations meet enterprise quality standards before being deployed to the Expert Services community - Stay current on evolving platform capabilities and techniques, rapidly incorporating new approaches that improve agent accuracy and efficiency Integrate AI Solutions with Professional Services GTM & Delivery - Understand the full professional services lifecycle—from pre-sales scoping and estimation through delivery execution and go-live—and ensure AI agent capabilities map to real engagement workflows - Design AI solutions that support accurate estimation by providing data on automated vs. manual effort, enabling services sales teams to right-size engagements - Partner with delivery consultants to validate that AI-generated outputs are usable in real customer contexts, incorporating feedback into continuous improvement cycles - Contribute to packaging AI-accelerated delivery into repeatable service offerings that can be positioned and sold by services and license sales teams Build Platform Integrations & Delivery Automation - Integrate AI agent outputs with the ServiceNow platform, customer engagement portals, and internal delivery systems to create seamless end-to-end automation - Design APIs, data pipelines, and integration patterns that connect autonomous implementation tools with estimation systems, resource management platforms, and project tracking tools - Build automated testing and validation workflows that verify AI-generated configurations against ServiceNow best practices and customer requirements before deployment - Collaborate with the implementation platform team to embed AI capabilities into the customer and partner delivery experience - Ensure all integrations meet enterprise security, data governance, and compliance standards - Coordinate with the platform administrator on release management—staging validation, production rollout, and vendor escalation—so new AI capabilities reach users without disrupting platform stability Drive Measurement & Continuous Improvement - Establish quality metrics for AI agent outputs: accuracy rates, rework percentages, time savings, and customer acceptance rates, feeding these signals into the adoption and ROI metrics the platform administrator reports to A&M leadership - Analyze agent performance data to identify improvement opportunities, failure patterns, and expansion use cases - Contribute to the delivery acceleration roadmap by identifying where AI can fill capability gaps or replace manual processes - Document engineering best practices, architectural patterns, and lessons learned to build organizational knowledge - Participate in sprint ceremonies, code reviews, and cross-team collaboration in a two-week sprint cadence with monthly releases Qualifications To be successful in this role you have: - 5+ years of experience in software engineering, AI/ML engineering, or technical consulting in enterprise software environments - 2+ years of hands-on experience with large language models, prompt engineering, and AI agent development—not just using AI tools, but building production systems on top of them - Demonstrated expertise in prompt engineering techniques: chain-of-thought reasoning, structured output generation, few-shot/zero-shot patterns, context window management, and systematic prompt evaluation - Strong understanding of professional services delivery operations: how engagements are scoped, sold, estimated, staffed, and delivered - Experience with API design, system integration, and building data pipelines that connect AI outputs to enterprise workflows - Proficiency in Python, JavaScript/TypeScript, or similar languages used in AI agent development and automation - Understanding of ServiceNow platform architecture, data models, and configuration patterns - Excellent communication skills—ability to translate technical AI capabilities into business impact for non-technical stakeholders - Experience working in agile, sprint-based environments with measurable delivery outcomes Not required but nice to have: - Experience building autonomous implementation or code generation systems that produce production-ready outputs - Background in management consulting or professional services delivery operations - Familiarity with ServiceNow implementation methodology and delivery best practices - Experience with AI agent orchestration frameworks and multi-step workflow automation - Knowledge of AI ethics, output validation, responsible AI practices, and enterprise governance requirements - ServiceNow platform certifications (CSA, CIS, or similar) - Experience with enterprise estimation tools, resource management platforms, or delivery automation systems Additional Information Work Personas We approach our distributed world of work with flexibility and trust. Work personas (flexible, remote, or required in office) are categories that are assigned to ServiceNow employees depending on the nature of their work and their assigned work location. Learn more here. To determine eligibility for a work persona, ServiceNow may confirm the distance between your primary residence and the closest ServiceNow office using a third-party service. Equal Opportunity Employer ServiceNow is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, creed, religion, sex, sexual orientation, national origin or nationality, ancestry, age, disability, gender identity or expression, marital status, veteran status, or any other category protected by law. In addition, all qualified applicants with arrest or conviction records will be considered for employment in accordance with legal requirements. Accommodations We strive to create an accessible and inclusive experience for all candidates. If you require a reasonable accommodation to complete any part of the application process, or are unable to use this online application and need an alternative method to apply, please contact [email protected] for assistance. Export Control Regulations For positions requiring access to controlled technology subject to export control regulations, including the U.S. Export Administration Regulations (EAR), ServiceNow may be required to obtain export control approval from government authorities for certain individuals. All employment is contingent upon ServiceNow obtaining any export license or other approval that may be required by relevant export control authorities. From Fortune. ©2025 Fortune Media IP Limited. All rights reserved. Used under license. - Employee Type: Regular - Region: AMS - North America and Canada - Work Persona: Flexible or Remote

Company Description It all started in sunny San Diego, California in 2004 when a visionary engineer, Fred Luddy, saw the potential to transform how we work. Fast forward to today — ServiceNow stands as a global market leader, bringing innovative AI-enhanced technology to over 8,100 customers, including 85% of the Fortune 500®. Our intelligent cloud-based platform seamlessly connects people, systems, and processes to empower organizations to find smarter, faster, and better ways to work. But this is just the beginning of our journey. Join us as we pursue our purpose to make the world work better for everyone. Job Description ROLE DESCRIPTION As a Sr. Delivery Acceleration AI Engineer, you will design, develop, and optimize AI-powered autonomous implementation solutions that transform how ServiceNow Expert Services deliver customer implementations. Working within the Delivery Acceleration team, you’ll focus on building and refining AI agents that automate ServiceNow configuration, generate implementation artifacts, and accelerate time-to-deploy—turning what previously required weeks of manual effort into AI-driven delivery that produces production-ready outputs in hours. This role requires deep expertise in prompt engineering, AI agent architecture, and an understanding of enterprise professional services delivery. You’ll work directly with autonomous implementation platforms built on large language models to create, test, and refine the AI-driven workflows that generate ServiceNow configurations, user stories, test scripts, and deployment packages for customer engagements. Critically, you must understand the professional services go-to-market motion—how services are scoped, sold, estimated, and delivered—because the AI solutions you build must align with how consultants and sales teams position and execute customer engagements. Your work directly impacts delivery speed, quality, margin, and the customer experience. Success requires balancing technical depth in AI/LLM systems with practical business acumen. You’ll operate in a fast-paced sprint cadence where AI capabilities evolve rapidly, requiring continuous experimentation, rigorous quality validation, and close collaboration with solution architects, product managers, and delivery consultants across AMS, EMEA, and APAC+JPN. You will partner closely with the platform administrator who owns operations, adoption, and governance for the AI-powered deal and delivery document generator, ensuring the AI agents and prompt assets you build are deployed, scaled, and governed effectively across the global delivery community. WHAT YOU GET TO DO IN THIS ROLE: Design & Develop AI-Powered Implementation Agents - Architect and build AI agent workflows that autonomously generate ServiceNow configurations, implementation plans, user stories, and test scripts from customer requirements - Develop, test, and iterate sophisticated prompt chains and orchestration patterns that produce consistent, production-quality outputs across ServiceNow product workflows (ITSM, CSM, HRSD, SPM, etc.) - Design multi-step agentic processes that handle complex implementation logic—scope validation, dependency mapping, configuration generation, and quality assurance—with minimal human intervention - Build and maintain prompt libraries, templates, and reusable patterns that encode delivery best practices and Gold Implementation standards into AI agent behavior, partnering with the platform administrator on library structure, versioning, and publication to end users - Partner with AI Architects and Solution Architects to ensure agent outputs align with ServiceNow platform strategy, product direction, and enterprise readiness standards Lead Prompt Engineering & AI Quality Optimization - Serve as a subject matter expert in prompt engineering techniques for large language models, including chain-of-thought reasoning, few-shot learning, structured output generation, and context window optimization - Design and execute systematic prompt evaluation frameworks that measure output accuracy, consistency, completeness, and adherence to ServiceNow implementation standards - Continuously optimize prompt performance through A/B testing, output analysis, and iterative refinement—treating prompts as production code with version control and quality gates, incorporating user feedback and quality-audit signals surfaced by the platform administrator and the champions network - Develop guardrails and validation logic that ensure AI-generated configurations meet enterprise quality standards before being deployed to the Expert Services community - Stay current on evolving platform capabilities and techniques, rapidly incorporating new approaches that improve agent accuracy and efficiency Integrate AI Solutions with Professional Services GTM & Delivery - Understand the full professional services lifecycle—from pre-sales scoping and estimation through delivery execution and go-live—and ensure AI agent capabilities map to real engagement workflows - Design AI solutions that support accurate estimation by providing data on automated vs. manual effort, enabling services sales teams to right-size engagements - Partner with delivery consultants to validate that AI-generated outputs are usable in real customer contexts, incorporating feedback into continuous improvement cycles - Contribute to packaging AI-accelerated delivery into repeatable service offerings that can be positioned and sold by services and license sales teams Build Platform Integrations & Delivery Automation - Integrate AI agent outputs with the ServiceNow platform, customer engagement portals, and internal delivery systems to create seamless end-to-end automation - Design APIs, data pipelines, and integration patterns that connect autonomous implementation tools with estimation systems, resource management platforms, and project tracking tools - Build automated testing and validation workflows that verify AI-generated configurations against ServiceNow best practices and customer requirements before deployment - Collaborate with the implementation platform team to embed AI capabilities into the customer and partner delivery experience - Ensure all integrations meet enterprise security, data governance, and compliance standards - Coordinate with the platform administrator on release management—staging validation, production rollout, and vendor escalation—so new AI capabilities reach users without disrupting platform stability Drive Measurement & Continuous Improvement - Establish quality metrics for AI agent outputs: accuracy rates, rework percentages, time savings, and customer acceptance rates, feeding these signals into the adoption and ROI metrics the platform administrator reports to A&M leadership - Analyze agent performance data to identify improvement opportunities, failure patterns, and expansion use cases - Contribute to the delivery acceleration roadmap by identifying where AI can fill capability gaps or replace manual processes - Document engineering best practices, architectural patterns, and lessons learned to build organizational knowledge - Participate in sprint ceremonies, code reviews, and cross-team collaboration in a two-week sprint cadence with monthly releases Qualifications To be successful in this role you have: - 5+ years of experience in software engineering, AI/ML engineering, or technical consulting in enterprise software environments - 2+ years of hands-on experience with large language models, prompt engineering, and AI agent development—not just using AI tools, but building production systems on top of them - Demonstrated expertise in prompt engineering techniques: chain-of-thought reasoning, structured output generation, few-shot/zero-shot patterns, context window management, and systematic prompt evaluation - Strong understanding of professional services delivery operations: how engagements are scoped, sold, estimated, staffed, and delivered - Experience with API design, system integration, and building data pipelines that connect AI outputs to enterprise workflows - Proficiency in Python, JavaScript/TypeScript, or similar languages used in AI agent development and automation - Understanding of ServiceNow platform architecture, data models, and configuration patterns - Excellent communication skills—ability to translate technical AI capabilities into business impact for non-technical stakeholders - Experience working in agile, sprint-based environments with measurable delivery outcomes Not required but nice to have: - Experience building autonomous implementation or code generation systems that produce production-ready outputs - Background in management consulting or professional services delivery operations - Familiarity with ServiceNow implementation methodology and delivery best practices - Experience with AI agent orchestration frameworks and multi-step workflow automation - Knowledge of AI ethics, output validation, responsible AI practices, and enterprise governance requirements - ServiceNow platform certifications (CSA, CIS, or similar) - Experience with enterprise estimation tools, resource management platforms, or delivery automation systems Additional Information Work Personas We approach our distributed world of work with flexibility and trust. Work personas (flexible, remote, or required in office) are categories that are assigned to ServiceNow employees depending on the nature of their work and their assigned work location. Learn more here. To determine eligibility for a work persona, ServiceNow may confirm the distance between your primary residence and the closest ServiceNow office using a third-party service. Equal Opportunity Employer ServiceNow is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, creed, religion, sex, sexual orientation, national origin or nationality, ancestry, age, disability, gender identity or expression, marital status, veteran status, or any other category protected by law. In addition, all qualified applicants with arrest or conviction records will be considered for employment in accordance with legal requirements. Accommodations We strive to create an accessible and inclusive experience for all candidates. If you require a reasonable accommodation to complete any part of the application process, or are unable to use this online application and need an alternative method to apply, please contact [email protected] for assistance. Export Control Regulations For positions requiring access to controlled technology subject to export control regulations, including the U.S. Export Administration Regulations (EAR), ServiceNow may be required to obtain export control approval from government authorities for certain individuals. All employment is contingent upon ServiceNow obtaining any export license or other approval that may be required by relevant export control authorities. From Fortune. ©2025 Fortune Media IP Limited. All rights reserved. Used under license. - Employee Type: Regular - Region: AMS - North America and Canada - Work Persona: Flexible or Remote

• Build and maintain scalable data pipelines and transformation workflows • Implement data quality checks, validation frameworks, and monitoring systems • Design and operationalize evaluation frameworks for datasets and ML outputs • Package and deliver production-ready datasets with clear documentation and QA standards • Develop ML-assisted tools and workflows to improve data processing and delivery efficiency • Generate, augment, and validate synthetic datasets to support client and internal use cases • Deploy lightweight ML/LLM-powered solutions to solve operational bottlenecks • Work directly with delivery teams to implement and maintain production workflows • Debug, troubleshoot, and resolve technical issues across data pipelines and systems • Continuously improve tooling, processes, and measurement approaches used in delivery • Identify and implement practical improvements that increase speed, reliability, and quality of delivery outcomes