AI Engineer
Lead the development and implementation of AI and machine learning solutions on the Azure platform. Build and operationalize Generative AI applications, including RAG solutions and intelligent assistants.
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Lead the development and implementation of AI and machine learning solutions on the Azure platform. Build and operationalize Generative AI applications, including RAG solutions and intelligent assistants.
Design and develop end-to-end NLP pipelines and agentic architectures to power intelligent contact center automation. Optimize RAG systems, manage conversation memory, and integrate AI components into scalable production microservices.
Design, deploy, and monitor end-to-end Machine Learning and Generative AI solutions. Process data sources to extract business insights and build prototypes using cutting-edge tools.
You will develop and integrate AI models into production environments while collaborating with multidisciplinary teams to create intuitive digital products. Your daily tasks involve problem-solving, backend API development, and driving innovation through advanced AI technologies.
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You will design, build, and operate scalable AI systems, including generative AI applications and RAG workflows, to enhance product capabilities. Additionally, you will establish technical standards for AI development, evaluation, and deployment while collaborating across cross-functional teams.
Lead a team of AI engineers to design, build, and deploy production-grade AI services including LLMs, RAG, and agentic workflows. Own the end-to-end technical architecture, evaluation standards, and roadmap alignment with business stakeholders.
Design and develop Generative AI solutions using Amazon Bedrock and AWS cloud services to transition initiatives from experimentation to production. Collaborate with multidisciplinary teams to build scalable, secure, and maintainable enterprise AI architectures.
You will lead the architecture and development of production-grade AI agents and intelligence products to optimize payment processes. This involves setting technical direction for agentic systems, ensuring reliability, and mentoring engineers to deliver complex cross-team AI projects.
You will design, implement, and maintain an AI Platform and Internal Developer Platform to support development and data science teams. This role involves automating cloud resource provisioning and managing platform configurations through efficient workflows.
Own and define product areas across financial services including insurance, payments, and investments. Collaborate with engineering, design, and business teams to launch features and improve user journeys based on data and feedback.
You will own product areas within AI Investing, defining user problems, roadmaps, and success metrics. You will collaborate with engineering, design, and operations teams to launch features and iterate based on data and user feedback.
Own and manage product areas across financial services such as insurance, payments, and savings. Define product direction, success metrics, and roadmaps while collaborating with engineering, design, and operations teams to launch and iterate features.
The Product Manager will own specific product areas within the AI Stockbroking platform, defining user problems, roadmaps, and success metrics. They will collaborate with engineering, design, and business teams to launch features and iterate based on data and user feedback.
You will own product areas within the AI Stockbroking division, defining user problems, roadmaps, and success metrics. You will collaborate with engineering, design, and business teams to launch features and drive continuous product iteration.
Own and define product areas within AI Finance, including insurance, payments, and investments. Collaborate with engineering, design, and business teams to launch features, monitor performance, and drive iterative improvements.
Own product areas across financial services including insurance, payments, and investing while defining user problems and success metrics. Collaborate with engineering, design, and business teams to launch features and drive iterative improvements based on data and user feedback.
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You will own product areas across financial services like insurance and payments, defining roadmaps and success metrics. You will collaborate with engineering, design, and operations teams to launch features and drive continuous product improvements.
Build and scale backend services using Python, Go, or Node.js while contributing to full-stack features with TypeScript and React. Design APIs, real-time pipelines, and distributed systems while collaborating with cross-functional teams to deliver end-to-end solutions.
You will build and own production-grade AI agents and machine learning models that power real-time decisioning and customer interactions. The role involves managing the full lifecycle of these systems, from data engineering and model training to building internal dashboards and ensuring system security.
Build and ship mobile features for KIRA's AI Finance Agent across Android and iOS platforms. Collaborate with product and design teams to create intuitive flows for insurance, payments, and financial services.
Build and ship native Android features for an AI Neobank app using Kotlin and Jetpack Compose. Collaborate with product and design teams to simplify complex financial user journeys and integrate secure backend APIs.
Build and ship mobile features for an AI Neobank app across Android and iOS platforms. Collaborate with product and design teams to create intuitive financial service flows and improve app reliability.
Build and ship native Android features for an AI Finance Agent using Kotlin and Jetpack Compose. Collaborate with product and design teams to optimize user journeys and improve app performance and reliability.
Build and ship native Android features for an AI Finance Agent using Kotlin and Jetpack Compose. Collaborate with product and design teams to optimize user journeys and improve app performance and reliability.
Develop and optimize ML models from scratch while collaborating with cross-functional teams to deploy them into production. Establish experimentation roadmaps and maintain reproducible pipelines to ensure optimal model performance.
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The role involves building and shipping end-to-end AI features, turning raw model outputs into reliable product behaviors. You will design prompts, tools, and agent workflows while optimizing for latency, cost, and production reliability.
Design and operate the inference and orchestration layer to power AI interactions across mobile and desktop clients. Focus on optimizing latency, throughput, and reliability for production AI-powered features.
Build the product layer for AI-native workflows, focusing on agent design, tool integration, and system reliability. Develop end-to-end features across the frontend and backend to create proactive, goal-driven AI assistants.
Build AI-native systems, agents, and automation workflows to optimize financial services for a Neobank app. Design and implement reliable AI experiences for onboarding, KYC, risk review, and operations while managing constraints like latency and accuracy.
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