JavaScript AI Jobs

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Own the full product development lifecycle for new platform capabilities and product experiences end-to-end. Collaborate closely with internal customers to understand their problems and implement effective solutions. Work with the research team to share relevant feedback and iterate on applying their latest models.

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As a Software Engineer on the Monetization Delivery team, you will architect, build, and optimize the ads delivery platform that serves ads in real time at global scale. You will design systems aimed at ensuring correctness, safety, and continuous optimization under heavy load. Your work will involve developing decision engines, ranking logic, and delivery pipelines that require strong performance, reliability, and privacy guarantees. You will partner with Product, Design, and Research teams to define requirements and drive novel solutions to highly complex technical problems. The role includes prototyping, experimenting, and deploying rapid iterations to improve delivery quality, relevance, and efficiency. Additionally, you will implement infrastructure and services that support ongoing measurement, optimization, and model-based improvements, ensuring operational excellence through monitoring, alerting, performance analysis, and rigorous testing. You will contribute to technical strategy and help shape the long-term roadmap of the ads delivery stack while building safety, fairness, and policy alignment into delivery systems from first principles.

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Design, build, and operate scalable back-end systems that power real-time, AI-driven chat experiences. Own mission-critical services and infrastructure, delivering impactful features from ideation through to production. Push the boundaries of applied AI by enabling new agent capabilities, workflows, and system behaviours. Shape how engineering standards, architecture, and processes are built and scaled. Mentor and support engineers across the team, raising the bar for technical quality and ownership. Set and uphold high standards for code quality, performance, reliability, and security. Collaborate closely with product, design, and leadership to align technical direction with business outcomes.

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Design and implement AI agents and extend existing agents with new capabilities including managing agent context using techniques like sub-agents and retrieval-based context management. Develop complex tools for agents such as computer use and browser use. Research and develop multi-agent orchestration and tool calling systems to enable collaboration between agents. Build and maintain production-grade APIs and AI-powered features across backend services and user-facing experiences. Evaluate AI performance through tests and evaluations and iterate on prompts, agent tools, and orchestration to improve output quality and reliability.

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Design, build, and own backend systems end-to-end, including services, APIs, data pipelines, and infrastructure that power products. Solve complex technical challenges across distributed systems, scaling, concurrency, and performance. Integrate and operate large generative AI models in production—deploying, serving, and scaling systems that combine internal research and external capabilities to unlock new product experiences. Instrument, experiment, and iterate in production to continuously improve system and product quality. Design and operate core platform infrastructure, including integrations with third-party providers, storage systems, security, and internal APIs.

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Lead development of advanced prompt engineering and retrieval pipelines by architecting and building scalable solutions that handle thousands of customer conversations daily across integrations such as Zendesk, Intercom, and Salesforce. Leverage generation pipelines to deliver rapid insights, accurate analysis, and meaningful customer interaction scoring. Architect real-time multimodal simulations to own the development of realistic, interactive training experiences across voice, video, and chat using platforms like OpenAI, ElevenLabs, and Vapi, ensuring simulations dynamically adapt to user input for immersive learning environments. Drive high-performance user experiences by setting technical standards for intuitive, lightning-fast interfaces built with Next.js, ensuring UIs handle complex AI interactions seamlessly under demanding workloads, and mentor others to achieve similar standards.

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Lead development of advanced prompt engineering and retrieval pipelines by architecting and building scalable solutions that handle thousands of customer conversations daily across integrations like Zendesk, Intercom, and Salesforce, leveraging cutting-edge generation pipelines for rapid insights, accurate analysis, and meaningful customer interaction scoring. Architect real-time multimodal simulations by owning the development of realistic, interactive training experiences across voice, video, and chat using platforms like OpenAI, ElevenLabs, and Vapi, with simulations dynamically adapting to user input to create immersive learning environments. Drive high-performance user experiences by setting technical standards for intuitive, fast interfaces built with Next.js, ensuring UIs handle complex AI interactions seamlessly under demanding workloads, and mentoring other engineers to achieve the same technical standards. Shape technical decisions, own major parts of the product, mentor teammates, and push personal skills in full-stack development including frontend, backend, and AI integrations, making critical decisions about architecture, tooling, and product direction.

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In this role, you will own the end-to-end development lifecycle for new platform capabilities and integrations with other systems, collaborate closely with engineers, data scientists, information systems architects, and internal customers to understand their problems and implement effective solutions, and work with product and research teams to share relevant feedback and iterate on applying their latest models.

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Serve as WRITER's embedded technical AI specialist onsite, building strong daily relationships with client engineering, AI COE, and business teams, acting as the primary point of contact for all WRITER-related technical matters. Own the end-to-end release workflow from WRITER platform updates through production deployment across all client environments, including coordinating dual-track updates, making critical go/no-go decisions, and providing hands-on troubleshooting. Design, implement, and maintain the client's custom front-end setup, production retrieval, and agentic systems, rigorously testing, validating, and troubleshooting AI-specific features like LLM applications, RAG performance, and prompt engineering. Navigate client security, risk, and compliance approval processes by working with Information Security teams to obtain necessary approvals, documenting compliance artifacts, and streamlining workflows to meet regulatory requirements. Reduce operational pain points, contribute to long-term migration strategies for clients towards standard WRITER-managed environments, and gather real-world deployment feedback to influence WRITER's product direction strategically.

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Help users discover and master the Dataiku platform through user training, office hours, demos, and ongoing consultative support. Analyse and investigate various kinds of data and machine learning applications across industries and use cases. Provide strategic input to the customer and account teams that help make customers successful. Scope and co-develop production-level data science projects with customers. Mentor and help educate data scientists and other customer team members to aid in career development and growth.