JavaScript AI Jobs

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The AI Agent Engineer is responsible for building and deploying AI agents including prompt design, workflow configuration, integrations, telephony setup, and evaluation frameworks. The role involves acting as the primary technical partner for customers by leading regular demos, communicating progress, gathering feedback, and guiding solutions from concept to production. It includes configuring and connecting systems using APIs, handling authentication, data mapping, error handling, and integrating with CRMs, knowledge bases, and other enterprise tools. The engineer sets up telephony systems including SIP/CCaaS/PSTN routing, passes metadata, configures fallbacks, and troubleshoots call quality. Responsibilities also include writing and refining prompts for LLM-driven agents, monitoring their performance, conducting iterative testing, and ensuring agents meet automation and containment targets. The role requires translating customer requirements into actionable solutions and working consultatively to resolve challenges related to security, connectivity, or knowledge ingestion. Additionally, the engineer collaborates with product and engineering teams to escalate platform gaps, resolve technical issues, and independently drive leading client implementations.

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Design, architect, and operate scalable services and APIs that power the LLM compliance platform. Architect how AI insights are surfaced to users, ensuring the system is robust, fast, and intuitive. Make high-impact technical decisions quickly. Challenge "why" and "how" to ensure delivery of the best possible experience for users. Shape engineering culture, standards, and tooling as the company grows. Own end-to-end technical decisions including designing systems, architecting solutions, shipping to production, and iterating based on customer feedback.

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Serve as the primary technical subject matter expert on OpenAI Codex for a portfolio of customers, embedding deeply with them to enable their engineering teams and build coding workflows. Partner directly with customers to design and implement AI-enhanced development workflows, from rapid prototyping through scalable production rollout. Build high-quality demos, reference implementations, and workflow automations, using Codex itself as part of the development process. Lead large-format workshops, technical deep dives, and hands-on enablement sessions that help engineering organizations adopt AI coding tools effectively and safely. Contribute technical content including examples, guides, patterns, and best practices to the OpenAI Cookbook to help the broader developer community accelerate their work with Codex. Gather high-fidelity product insights from real customer deployments and translate them into clear product proposals and model feedback for internal teams. Influence customer strategy and decision-making by framing how AI coding tools fit into their software development lifecycle, technical roadmap, and organizational workflows. Serve as a trusted advisor on solution architecture, operational readiness, model configuration, security considerations, and best-practice adoption.

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Work on a small, high-caliber team building AI products for clients, from requirements gathering and prototyping through system design, development, testing, and deployment. Own features end-to-end and develop domain expertise across a range of AI use cases. Spend most of the time coding and frequently interact with clients to ensure the solutions meet their needs.

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You will work on a small, high-caliber team building AI products for clients, setting technical direction, writing code, and serving as the go-to person when challenges arise. Spend approximately 75% of your time coding and 25% interacting with clients, including CTOs, to understand problems, evaluate tradeoffs, and ensure solutions meet their needs.

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As a member of the Bots team, design, build, and scale systems that enhance user engagement with the AI-powered platform, including bot chat orchestration, AI image generation, AI video generation, and tooling for managing these features. Collaborate with cross-functional teams like product managers, designers, and data specialists to deliver high-quality, performant, and maintainable features. Experiment with and integrate new AI image, video, and voice generation technologies. Build tooling and infrastructure around various AI technologies. Gain exposure to the architecture and operations of a fast-growing social AI product. Contribute expertise to evolve team processes and technical infrastructure, ensuring scalability and reliability.

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Debug and fix issues in the platform and ship PRs 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 drive AI adoption.

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Ship critical infrastructure by managing real-world logistics and financial data for the largest enterprise in the world. Own the why by building deep context through customer calls and understanding Loop’s value to customers, pushing back on requirements if a better, faster solution exists. Work across system boundaries with full-stack proficiency, including frontend UX, LLM agents, database schema, and event infrastructures. Leverage AI tools to automate boilerplate work, focusing on quality, architecture, and product taste. Constantly optimize development loops, refactor legacy patterns, automate workflows, and fix broken processes to raise the velocity bar.

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As a Software Engineer at Mirage, you will work across product engineering, backend/platform engineering, and applied AI teams. Responsibilities include designing and building systems, APIs, and infrastructure that power products; solving challenges involving distributed systems, scaling, and performance; integrating and operating large AI models in production; building core platform components such as storage, billing, observability, and security; shipping end-to-end product experiences for creative workflows; building polished, performant user interfaces (web or native mobile); pushing the boundaries of video, graphics, and AI-powered creation tools; instrumenting, A/B testing, and iterating quickly with real user data; building and shipping AI-powered product experiences end-to-end; working with state-of-the-art models across video, audio, image, and text; designing systems for context, reasoning, and intelligent behavior; and building evals, datasets, and tooling for improving model quality.

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Lead and grow a team of Forward Deployed Engineers (FDE) delivering production systems with frontier models, owning end-to-end delivery outcomes through clarity, speed, tight coordination, and technical quality. Codify effective practices into tools, playbooks, and roadmap inputs to create leverage for OpenAI and the wider developer community. Monitor early indicators in product behavior, customer environments, or delivery practices and raise them with urgency. Use judgment to determine what requires action and set high performance standards for the FDE team while supporting individual growth through direct and actionable feedback. Define staffing and support strategies for scalable field teams without added complexity.