Staff Forward Deployed AI Engineer

We are looking for a Staff-level Forward Deployed AI Engineer to design, build, and deliver AI-powered applications that create measurable business impact. This is a hands-on engineering role with strong design responsibility — you will spend most of your time writing code, integrating systems, and taking solutions to production, while also shaping practical, scalable designs that ensure what you build can operate reliably at enterprise scale. You will work closely with business stakeholders to identify high-value opportunities, rapidly prototype solutions, and evolve them into well-architected, production-grade systems. What You Will Be Responsible For You will play a lead technical role in designing and delivering AI-enabled solutions across the enterprise. Build & Ship AI Applications (Primary Focus)Design, develop, and deploy AI-powered applications and workflowsWrite production-quality code across:Backend services and APIsAI orchestration layers and agentsEnterprise integrationsRapidly prototype solutions and iterate them into scalable production systemsOwn delivery end-to-end: build, test, deploy, monitor, and improve Design Practical, Scalable AI SystemsTranslate use cases into clear, implementable system designsMake architecture decisions that balance:Speed of deliveryScalability and reliabilityCost and operational efficiencyDefine patterns for:API-first integrationsAI orchestration and workflowsReusable services and componentsEnsure systems are simple enough to build quickly, but structured enough to scale Integrate AI into Real Enterprise WorkflowsEmbed LLM capabilities into products, internal tools, and business processesBuild and maintain APIs and system integrationsImplement agent workflows and orchestration logic that solve real operational problemsOptimize systems for performance, resilience, and cost efficiency Partner with Business & Deliver OutcomesWork directly with stakeholders to understand problems and validate solutionsTranslate requirements into working software quickly (days/weeks, not months)Iterate based on feedback and usage to drive measurable impact Contribute to Engineering Standards & ReuseBuild and contribute to shared libraries, templates, and servicesEstablish practical patterns based on real implementationsHelp evolve internal platforms through code and working solutions, not just design artifacts Build Within a Governed AI EnvironmentImplement secure and reliable AI solutions in practice, including:Prompt safety and validationInjection/misuse preventionObservability and traceabilityAlign implementations with enterprise security, privacy, and compliance requirements Technology Environment Cloud & Platform: Microsoft ecosystem (Azure)AI Models: Claude and other enterprise-approved LLMsArchitecture Style: API-first, event-driven, and modular servicesCore Focus:AI application engineeringOrchestration and agent workflowsEnterprise integrations What You Bring Hands-On Engineering Strength (Critical) Proven ability to build and ship production systems at scaleStrong experience in:Backend development and API designCloud-native systems (Azure preferred)Integration-heavy, distributed applicationsComfortable operating in a high-output, hands-on environment System Design & Architecture Judgment Ability to design clean, practical architectures that support real-world constraintsExperience making trade-offs across:delivery speed vs scalabilitysimplicity vs flexibilityCan move fluidly between coding and design thinking AI / GenAI Development Hands-on experience building LLM-powered applications in productionStrong understanding of:Prompt design and evaluationAgent-based workflows and orchestrationIntegrating AI into production systemsAbility to debug, tune, and improve AI behavior in code Execution Mindset Bias toward shipping and learning from production usageComfortable moving from idea → prototype → productionStrong ownership: you build it, you run it We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.