React AI Jobs

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As a Full Stack Software Engineer at Replicant, you will design and deliver technology that powers natural, human-like conversations at scale to help companies reduce wait times, improve customer satisfaction, and empower representatives to focus on complex problems. You will build rich user experiences and backend services that enable customers to design, launch, and monitor AI-powered conversations. Responsibilities include building new features for Replicant's core AI voice and chat products handling millions of daily conversations, shipping full stack end-to-end features quickly, integrating automatic speech recognition, text to speech, and conversational AI model improvements into products, refactoring, optimizing, and debugging production systems balancing latency, cost, and user experience, participating in regular on-call rotations monitoring live systems, continuously improving systems based on performance metrics and customer feedback, shaping a culture emphasizing knowledge sharing and mentorship across distributed systems and enterprise-scale AI design, and participating in team and company-wide office events with travel required.

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Ship production-grade backend and frontend features for core member and provider flows using React, TypeScript, APIs, and data layers, ensuring high polish and reliability. Own features end-to-end, including specification, building, testing, deployment, monitoring, and handling complex state, permissions, and edge cases. Build and maintain robust system hygiene, including instrumentation, dashboards and alerts, CI/CD pipelines, code reviews, and production debugging. Design, implement, and maintain AI-powered workflows comprising tool/function calling, structured outputs, Retrieval-Augmented Generation (RAG), evals, tracing, observability, prompt versioning, and guardrails. Build and operate workflow and agent flows using orchestration patterns similar to Temporal, Dagster, or Airflow, managing retries, idempotency, asynchronous job queues, and failure handling. Collaborate closely with cross-functional partners to deliver reliable, scalable, and user-centric healthcare products.

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The Applied AI engineer at Mistral works within the customer-facing technical team to deploy AI solutions that deliver measurable business impact. Responsibilities include identifying high-value internal use cases across various departments such as engineering, legal, HR, sales, and operations; building end-to-end LLM applications including prompts, RAG pipelines, APIs, simple UIs, deployment, and monitoring; owning the full lifecycle of AI tools from prototype to production, maintenance, and iteration; documenting learnings and sharing insights with product and research teams; and converting successful internal tools into customer demos or case studies where appropriate. The role also involves acting as the first internal customer for these tools to identify edge cases and limitations, improving models through usage feedback.

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Collaborate closely with researchers, AI engineers, and product engineers on complex customer projects, integrating cutting-edge AI models into clients' software products. Design, develop, and maintain scalable and robust full-stack applications, ensuring seamless integration between front-end and back-end systems. Develop complex use cases with customers, providing guidance and ensuring the best production integration with back-end and front-end interfaces. Collaborate with product and science teams to continuously improve product and model capabilities based on customer feedback.

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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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Own the technical architecture including backend, frontend, infrastructure, and AI integration. Write code daily to build critical systems. Make stack and design decisions shaping the product for years. Set standards for code quality, testing, and engineering discipline. Integrate large language models (LLMs) and AI workflows into the platform. Work directly with founders on product direction and the technical roadmap. Create clarity and structure in an environment lacking perfect specifications. Mentor and guide other developers technically.

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As a Senior Software Engineer (AI Voice Agents) at Heidi, you will work closely with the Engineering Manager and Product Lead to build end-to-end AI features including architecting and shipping fullstack solutions that leverage voice AI and large language models (LLMs) to automate clinical workflows. You will operationalize voice AI by implementing and fine-tuning audio processing pipelines to ensure that Automatic Speech Recognition (ASR) and LLM agents perform accurately in diverse, real-world medical environments. You will translate complex clinical feedback into technical solutions by rapidly prototyping and deploying improvements to model behavior, prompting strategies, and audio handling. Optimizing fullstack performance for real-time audio streaming and token generation to minimize latency for clinicians is a key responsibility. Additionally, you will act as a technical liaison for enterprise customers to bridge the gap between their complex infrastructure needs and the core platform, delivering seamless and scalable integrations within large healthcare environments. You will also partner with implementation and clinical teams to shorten feedback loops by shipping critical integrations and feature requests from concept to production swiftly.

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In this role, you will own the full product development lifecycle for new platform capabilities and product experiences end-to-end. You will collaborate closely with internal customers to understand their problems and implement effective solutions. Additionally, you will work with the research team to share relevant feedback and iterate on applying their latest models.

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Senior Software Engineers at Lambda AI build end-to-end features for Lambda Cloud by contributing both frontend and backend code to existing and new customer-facing products. They collaborate across teams to deliver critical features for major customers, own production features and systems, and engage directly with client engineering teams and internal stakeholders.

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Serve as a public-facing expert and ambassador for Bolt.new across various social channels, offering real-time technical support and engagement to users. Create and improve user resources, surface community insights, and advocate for user needs with internal teams.