AI Vibe Coding Engineer
Rapidly prototype and iterate on LLM-powered applications and workflows using AI-assisted coding tools. Collaborate with product and UX teams to build demos, internal tools, and next-generation user experiences.
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Rapidly prototype and iterate on LLM-powered applications and workflows using AI-assisted coding tools. Collaborate with product and UX teams to build demos, internal tools, and next-generation user experiences.
The Android Software Engineer will build and maintain production-grade mobile applications while integrating AI-assisted capabilities to improve user experience. They will collaborate with cross-functional teams to ensure application performance, scalability, and security across insurance and financial products.
The engineer will build and evolve mobile applications for insurance and financial products using Swift. They will also integrate AI-assisted capabilities to improve user experience and operational efficiency.
You will build core web experiences like Chat, Notes, and Calendar while integrating AI capabilities directly into product workflows. You are responsible for owning frontend performance, reliability, and accessibility across complex, highly interactive surfaces.
Design and lead the development of core backend services, APIs, and service integrations to support AI capabilities. Establish security standards, ensure HIPAA compliance, and drive engineering best practices across the platform.
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You will design and own the end-to-end Generative AI platform, including model serving, agent frameworks, and evaluation pipelines. Additionally, you will lead the integration of AI into physical manufacturing processes and robotic systems to improve vehicle production.
You will lead and execute core 0-to-1 initiatives in AI, translating strategic vision into concrete execution roadmaps. You will architect scalable solutions and drive rapid implementation from prototype to production.
You will lead and execute core 0-to-1 initiatives in AI infrastructure, translating strategic vision into concrete execution roadmaps. You will architect scalable solutions and drive rapid implementation from prototype to production.
Lead platform estate modernization and sovereign cloud engagements by designing secure, scalable, and resilient architectures for commercial customers. Drive technical workshops, rapid prototyping, and proofs of concept to resolve technical blockers and influence customer deployment decisions.
The Enterprise AI and Integration Engineer is responsible for designing, building, and implementing AI agents, automation workflows, and enterprise system integrations. This role manages the end-to-end lifecycle of technical solutions, from proof of concept through deployment and ongoing support.
Design, train, and deploy reinforcement learning-based systems for complex decision-making problems. Ensure the stability, safety, and ongoing improvement of RL solutions as they transition from research to production environments.
The Lead AI Application Security Engineer will serve as the technical lead for securing GXO's Enterprise AI Platform and AI-powered applications. Responsibilities include defining AI security architecture, conducting AI red teaming, and integrating AI-aware DevSecOps practices into CI/CD pipelines.
You will architect and build developer-facing tools such as IDE integrations, CLIs, and CI/CD workflows to enhance engineering productivity. Additionally, you will integrate AI capabilities into developer workflows and mentor junior engineers on software craftsmanship.
Drive technical sales and adoption of Microsoft's AI and cloud platforms through hands-on engagements like hackathons and architecture workshops. Collaborate with developers and engineering teams to design secure, scalable solutions and resolve technical blockers.
You will partner with the People & Talent team to design and build AI-powered workflows that automate manual, high-friction HR processes. This involves developing internal tools, integrating AI agents with existing systems, and ensuring secure, scalable operations.
You will lead the development and optimization of AI-driven test automation workflows using tools like Claude Code and Playwright. This involves building feedback loops between CI/CD pipelines and AI agents to automate test generation, execution, and maintenance at scale.
The engineer will embed with sub-teams to build and deploy agentic workflows that improve developer productivity across firmware, runtime, and simulation. They will also own the shared skills repository and internal agent tooling to ensure high-quality, evaluated automation within the engineering lifecycle.
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Design, build, and operate AI-powered infrastructure to connect go-to-market systems and automate manual workflows across sales, marketing, and customer success. Own the architecture of the GTM systems AI layer, including LLM integrations, retrieval pipelines, and serverless services.
Lead discovery sessions with stakeholders to translate complex business problems into Agentic AI solution designs. Architect multi-agent workflows and build technical prototypes while guiding implementation teams.
The role involves designing, configuring, and implementing Pega AI and Customer Decision Hub solutions to drive business engagement. You will be responsible for integrating LLMs, optimizing decisioning strategies, and ensuring AI governance across enterprise workflows.
You will work directly with customers to design, build, and deploy production-grade AI solutions using LLMs and agentic technologies. Additionally, you will act as a technical bridge between customer needs and internal product teams to influence engineering roadmaps.
Act as a primary technical architect to design and deliver scalable networking solutions for AI, cloud, and data center environments. Lead complex sales cycles by translating business requirements into technical strategies and mentoring junior engineering teams.
The AI Tool Support Engineer will manage model services, configure IAM policies, and provide T1/T2 helpdesk support for an AI-powered coding assistant. The role also involves white-glove application services, including architecture design help and application change management.
The AI Tool Support Engineer will manage model services, configure IAM policies, and provide T1/T2 helpdesk support for AI-powered coding tools. They will also handle white-glove application services, including architecture design help and change management.
The Staff Security Engineer will lead security architecture and implementation across cloud and AI platforms, ensuring systems are secure by design. They will partner with engineering teams to define security standards, threat model designs, and automate security controls within developer workflows.
You will lead the security architecture and implementation for cloud and AI platforms, ensuring secure-by-design principles across infrastructure and applications. The role involves building reusable security controls, conducting threat modeling, and partnering with engineering teams to drive adoption of security standards.
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You will co-lead the technical direction for AI security products and partner with cross-functional teams to build proactive security controls. This involves embedding with product teams to design, build, and deploy hardened security solutions for AI-enabled surfaces.
The AI Forward Deployed Engineer acts as a bridge between SensibleAI capabilities and customer outcomes by designing and implementing cross-product AI solutions. They collaborate with delivery and engineering teams to validate value, harden solutions for production, and codify reusable patterns for the OneStream ecosystem.
Drive technical sales and adoption of Microsoft's cloud data platforms through demos, hackathons, and architecture workshops. Collaborate with enterprise customers to design secure, scalable data solutions and resolve technical blockers.
The Staff Engineer will integrate cutting-edge AI models into existing platforms to enhance product capabilities and user experience. They will also design evaluation frameworks, monitor AI performance in production, and collaborate with the data science team on model fine-tuning.
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