Node.js AI Jobs

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The core responsibilities of the Software Engineer, Enterprise Zone role include leading responses to critical incidents and customer-impacting events, working directly with enterprise customers, collaborating across engineering, product, and support teams to solve urgent problems, building internal tools and improving core product features based on real-world customer feedback. Additionally, responsibilities include building a new extensible platform for account and organization-level settings with declarative controls and AI guardrail controls, designing and implementing scalable backend architecture and APIs for asset cataloguing, ownership, and security, building unified interfaces for organizing and governing assets across accounts and products, embedding AI technology to monitor and optimize account management, driving technical alignment with senior leaders, delivering solutions and proofs of concept balancing short-term execution with long-term vision, tackling data standards and compliance automation challenges, building platforms like User Notifications, Audit Logs, Public APIs, supporting compliance and error tracking use cases, improving observability features such as SLOs and dashboards, and leading projects from start to finish while utilizing AI to enhance development and customer experience. These roles involve working cross-functionally, impacting premium plan sales, collaborating with multiple teams, and playing a key role in the company's growth with close connection to customers daily.

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The Software Engineer will own backend services that power core features across both Hiya mobile applications, including caller ID lookups, spam/fraud detection, call screening, real-time scam alerts, call transcription, and AI-generated summaries. Responsibilities include designing service architecture, writing production code, deploying to AWS, and operating systems at scale with high availability and low latency. The role also involves building and maintaining mobile integrations connecting backend services to iOS and Android apps, collaborating with mobile engineers to ensure seamless SDK behavior, debugging platform-specific issues, and shipping reliable features for millions of users. Additionally, the engineer will scale infrastructure to support growing user bases and new feature development, make architectural and implementation decisions balancing speed, quality, and long-term maintainability, solve ambiguous problems in call screening logic and backend structure, and collaborate across engineering, product, and design teams in a high-autonomy environment to ship impactful features.

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Lead the deployment, performance, and reliability of AI agents operating in live, high-stakes healthcare environments. Architect and scale full-stack systems integrating with EHRs, legacy healthcare platforms, and real-time voice infrastructure. Drive technical strategy for customer-facing solutions, collaborating with product and engineering to translate client needs into scalable architecture. Mentor engineers and set standards for code quality, testing, security, and HIPAA-compliant development. Shape product roadmap by identifying systemic challenges in customer workflows and proposing high-leverage technical solutions.

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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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Design, build, and operate scalable back-end systems that power AI agent and workflow builders. 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, workflow orchestration, and system behaviours. Shape how we build by influencing engineering standards, architecture, and processes as we scale. 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, 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 the engineering team builds by influencing engineering standards, architecture, and processes as the team scales. 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, 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, build, and operate scalable back-end systems that power AI agent and workflow builders. 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, workflow orchestration, and system behaviours. Shape engineering standards, architecture, and processes as the team scales. 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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As a Senior AI Engineer, you will drive intelligent features that redefine how users build automations by building AI-powered capabilities such as natural language input and smart suggestions to make creating workflows faster and more intuitive. You will collaborate across engineering, product, and design to integrate generative AI and LLM-based enhancements into the core user experience, improve existing AI integrations, develop new ones, and shape how AI powers the product. Responsibilities include architecting and implementing AI-powered capabilities like code generation, intelligent node creation, and workflow optimization; integrating LLM APIs and embedding models for text-to-workflow and natural language code suggestions; designing and iterating on prompts to improve model output and user experience; building internal tooling, evaluation benchmarks, and automated testing for AI components; collaborating closely with other engineers to ensure AI features are reliable, performant, and scalable; balancing experimentation with impact by shipping quickly with a focus on user value; and staying current with advances in LLMs, prompt frameworks, and developer tools to inform the product roadmap.

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Lead a team of engineers by helping them prioritize for impact, grow in their careers, and perform their best work. Own strategy, roadmap, and execution in close collaboration with product and design partners to decide on what to build and ensure delivery. Drive growth metrics such as activation rates, signups from integrations, and developer adoption by measuring and analyzing results. Ship products quickly and iterate by running experiments, learning from failures, and doubling down on successes. Build AI developer tools including MCP integrations and agentic builders, as well as platform integrations connecting Sanity to tools like Google Drive, Dropbox, and analytics platforms. Set technical direction and guide architecture decisions balancing velocity with maintainability across TypeScript, React, Node.js, and Go microservices. Collaborate with engineering leadership, marketing, and partnerships to align on shared growth metrics and goals.