JavaScript AI Jobs

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As a Vibe Code specialist on the Tendem project, you will own end-to-end data extraction workflows across complex websites, ensuring complete coverage, accuracy, and reliable delivery of structured datasets. You will leverage internal tools such as Apify and OpenRouter alongside custom workflows to accelerate data collection, validation, and task execution while meeting defined requirements. You must ensure reliable extraction from dynamic and interactive web sources by adapting approaches as needed to handle JavaScript-rendered content and changing site behavior. Responsibilities also include enforcing data quality standards through validation checks, cross-source consistency controls, adherence to formatting specifications, and systematic verification prior to delivery. Additionally, you will scale scraping operations for large datasets using efficient batching or parallelization, monitor failures, and maintain stability against minor site structure changes. Collaboration with Tendem Agents to handle repetitive tasks while providing critical thinking, domain expertise, and quality control to deliver accurate and actionable results is integral to this role.

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Own end-to-end data extraction workflows across complex websites, ensuring complete coverage, accuracy, and reliable delivery of structured datasets. Leverage internal tools (Apify, OpenRouter) alongside custom workflows to accelerate data collection, validation, and task execution while meeting defined requirements. Ensure reliable extraction from dynamic and interactive web sources, adapting approaches as needed to handle JavaScript-rendered content and changing site behavior. Enforce data quality standards through validation checks, cross-source consistency controls, adherence to formatting specifications, and systematic verification prior to delivery. Scale scraping operations for large datasets using efficient batching or parallelization, monitor failures, and maintain stability against minor site structure changes.

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As a Vibe Code specialist and AI Pilot on the Tendem project, you will own end-to-end data extraction workflows across complex websites, ensuring complete coverage, accuracy, and reliable delivery of structured datasets. You will leverage internal tools such as Apify and OpenRouter alongside custom workflows to speed up data collection, validation, and task execution while meeting defined requirements. You will ensure reliable extraction from dynamic and interactive web sources, adapting approaches to handle JavaScript-rendered content and changing site behavior. Your responsibilities include enforcing data quality standards through validation checks, cross-source consistency controls, adherence to formatting specifications, and systematic verification prior to delivery. You will scale scraping operations for large datasets using batching or parallelization, monitor failures, and maintain stability against minor site structure changes. Collaboration with Tendem Agents handling repetitive tasks and providing critical thinking, domain expertise, and quality control to deliver accurate results is also expected.

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Design, build, and own backend systems end-to-end, including services, APIs, data pipelines, and infrastructure that power the products. Solve complex technical challenges across distributed systems, scaling, concurrency, and performance. Integrate and operate large generative AI models in production by 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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Debug and fix issues in the platform and ship pull requests with fixes. Build internal tools and copilots powered by generative AI to enhance the team. Rapidly prototype proof-of-concepts for customer use cases. Collaborate across Engineering, Product, and Solutions teams to unblock customers and advance AI adoption.

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Work closely with the Product Lead as a Mid-level or Senior Fullstack Engineer operating at the intersection of core product development and clinical application, building end-to-end AI features including architecting and shipping fullstack solutions from React frontends to Python backend services that leverage voice AI and LLMs to automate clinical workflows. Implement and fine-tune audio processing pipelines to ensure Automatic Speech Recognition (ASR) and LLM agents perform accurately in diverse, real-world medical environments. Translate complex clinician feedback into technical solutions, rapidly prototyping and deploying improvements to model behavior, prompting strategies, and audio handling. Optimize fullstack performance to handle real-time audio streaming and token generation to minimize latency and create seamless conversational experiences for clinicians. Partner with implementation and clinical teams to quickly ship critical integrations and feature requests from concept to production in days rather than quarters.

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Build systems that integrate seamlessly with the EHRs used in American healthcare to feel like a native capability rather than a plugin. Develop systems that handle complex US healthcare billing rules, compliance requirements, and payer constraints so that clinicians do not have to manage these complexities. Write clean, testable code with strong interfaces, error handling, and observability for workflows depended on by clinicians and operators. Focus on outcomes that help clinicians and improve practice revenue, not just code functionality. Create AI-assisted workflow functionality that supports extraction, reconciliation, and drafting with human review, auditability, and clear controls. Collaborate closely with others through frequent pairing and shared design and implementation ownership. Learn about healthcare organizations' practical operations and US customer requirements to guide product improvements.

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As a Software Engineer at Magic, you will work on core systems or product surfaces that directly determine model capability and user experience. The role includes end-to-end ownership: defining problems, implementing solutions, shipping to production, and iterating based on real outcomes. Responsibilities may include building and scaling large distributed data pipelines for pre-training; designing filtering, mixture, and dataset versioning systems; developing post-training datasets, evaluation frameworks, and reward pipelines; running ablations that translate capability goals into measurable improvements; building end-to-end product surfaces that integrate deeply with the model; designing APIs, backend services, and frontend workflows for AI-first experiences; and improving reliability, observability, and performance of production systems. The position involves working with the unique technical challenges posed by long-context models such as internet-scale data acquisition, long-horizon post-training loops, and product workflows that make complex model behavior understandable and controllable. The role can evolve into specialization in data systems, post-training capability development, or product engineering leadership, depending on strengths and interests.

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Co-architect and co-build production AI agents with customer engineering teams. Own the technical win in pre-sales by designing POCs, answering deep technical questions, and guiding evaluations. Help customers deploy and operate agent-based applications such as conversational agents, research agents, and multi-step workflows. Advise customers post-sale on architecture, best practices, and roadmap-level decisions. Run technical demos, trainings, and workshops for developer audiences. Surface field feedback and contribute reusable patterns, cookbooks, and example code that scale across customers. Occasionally contribute code upstream when it meaningfully improves customer outcomes.

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Lead major cross-team platform initiatives, taking foundational systems from 0 → 1 and scaling them to support millions of users. Build shared, extensible Agent primitives that Replit Agent can reuse safely and consistently. Identify the highest-leverage technical bottlenecks such as performance, reliability, correctness, abuse, and observability, then design and ship solutions for scale. Raise the bar for engineering excellence through architecture reviews, code quality, reliability standards, and mentorship. Partner across teams to improve platform adoption, ergonomics, and velocity, turning platform work into measurable outcomes. Work on core areas including Connectors framework, content/configuration primitives, data/analytics/events and experimentation primitives, Identity & Access platform, Localization/i18n platform, Notifications & communications platform, and core web platform infrastructure including performance optimization, observability, debugging workflows, caching strategy, and reliability.