TypeScript AI Jobs

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As a Software Engineer on the AI Voice Agent team, you will work on real-time speech pipeline systems including live audio buffering, streaming, latency optimization, and integrating with speech providers. You will build and improve conversation intelligence systems that manage the LLM layer for natural conversation flow, including prompt construction, context management, function calling, and dialogue management. You will develop the action framework that allows the AI Voice Agent to execute tasks during calls such as querying account data, creating tickets, and checking order status, handling API configuration, success/failure branching, authentication management, and runtime execution. Additionally, you will work on knowledge ingestion, storage, and retrieval for the voice agent and manage memory for retaining information across conversations to improve responses. You will collaborate with designers to create easy-to-use interfaces for agent lifecycle management including creation, configuration, testing, and deployment. You will contribute to building evaluation frameworks and metrics for voice AI quality, post-call analytics, and instrumentation, as well as participate in the on-call rotation.

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As a Software Engineer on the AI Voice Agent team, you will work on real-time systems involving live audio such as buffering, streaming, and latency optimization, along with integrating speech providers. You will build and improve conversation intelligence systems, including prompt construction, context management, function calling, and dialogue management to make conversations feel natural. You will develop the action framework to execute configurable API calls, manage success/failure branching, authentication, and runtime execution during calls. You will work on knowledge ingestion, storage, retrieval, memory, and context for the voice agent to improve its performance over time. Additionally, you will collaborate on agent lifecycle tasks such as creation, configuration, testing, and deployment of voice agents and help build evaluation frameworks for model performance, call quality metrics, and call analytics. Participation in on-call rotations is also expected.

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As a Senior Software Engineer on the AI Voice Agent team, you will work on real-time systems involving live audio streaming and latency optimization integrated with speech providers. You will build and improve conversation intelligence systems that manage LLM layers, including prompt construction, context management, function calling, and dialogue management to create natural, actionable phone conversations. You will develop the action framework allowing configurable API calls with branching logic and runtime execution, supporting tasks like data lookup and ticket creation during calls. You'll manage knowledge ingestion, storage, and retrieval to enhance agent memory and learning over time. You will collaborate with designers to enable customers to create, configure, test, and deploy voice agents through intuitive product experiences. Additionally, you will help develop evaluation frameworks, analytics, call quality metrics, and monitoring instrumentation, and participate in on-call rotation duties.

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Implement and integrate AI functionality into key product features, craft and iterate on prompts to improve LLM reliability and usefulness, build AI-powered flows that feel intuitive and responsive to developers, evaluate and test AI outputs to ensure performance and accuracy, work alongside engineers to deliver robust, production-grade code, stay current with LLM tools, APIs, and best practices, deliver reliable, high-quality AI-powered product experiences, translate product needs into technical AI implementations, tune and test prompts for real-world use cases and developer workflows, collaborate closely with engineers and researchers, and contribute across frontend, backend, and integration layers.

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You will be building innovative customer support AI products by defining AI-first product development through UI/UX, capabilities, and data models. Day-to-day responsibilities include taking ownership of challenging problems from idea to production, working closely with coding agents as a core part of your workflow, building tooling and feedback systems that enhance their effectiveness, and exercising engineering judgment to determine when outputs are ready to ship or need iteration. Senior engineers will own features end-to-end, while staff-level engineers will have opportunities to shape the technical direction of the team.

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Build new LLM and instrumentation libraries for emerging LLM providers and agent frameworks. Maintain and enhance existing instrumentation across Python and TypeScript ecosystems and others such as OpenAI, Anthropic, LlamaIndex, CrewAI and more. Drive improvements to semantic conventions and OpenTelemetry standards that define AI observability. Collaborate with the global developer community through GitHub, Slack, and conferences, as well as with Arize PMs and solution architects. Take complex problems from ideation to completion with full ownership and accountability.

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The Full Stack Engineer is responsible for configuring and developing "skills" for foundation models like Claude and Gemini to automate content generation, marketing flows, and business processes; developing and scaling applications within the JavaScript/TypeScript ecosystem primarily using React and integrating AI agents and automation; creating automated content generation systems for platforms such as Substack, blogs, social media, and personalized email marketing; designing and implementing sophisticated automations using platforms like Make.com or n8n to bridge data between systems such as updating records in EHR tools like Cerbo; managing PostgreSQL databases (Neon/AWS) and handling deployments within a Linux/Bash-heavy environment; helping to implement and refine voice AI solutions for call overflows and appointment scheduling including GoHighLevel integrations; managing and deploying applications on AWS (EC2) with a focus on security and HIPAA compliance; configuring and implementing AI skills across various foundation models; collaborating with AI automation experts to design scalable, efficient solutions; and establishing coding standards and best practices for AI-driven development.

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The Product Engineer — Search at Firecrawl is responsible for owning the developer-facing search experience by shipping retrieval and ranking improvements from research as a usable product. The role involves shipping the entire product change including API updates, documentation, and examples. The engineer owns the search API end-to-end, ensuring the integration, usage, and build experience is smooth, covering response format, latency, error handling, pagination, and filtering. They use the API themselves to identify friction points before users do, closely monitor user feedback from GitHub, Discord, and support tickets, and translate research insights into product decisions in collaboration with the Search/IR and RL Research Engineers. Additionally, they run fast product experiments by hypothesizing, instrumenting, shipping, measuring, and iterating quickly to improve the search product. They are also expected to raise the bar on developer experience by fixing inconsistencies in response formats, error messages, and documentation proactively.

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Design and build AI agents that outperform human agents in managing complex customer interactions and driving customer retention. Identify cross-customer trends that guide the evolution of Decagon’s agent building platform and research efforts. Experiment with and run evaluations on the latest text and voice models, then integrate them at scale with large enterprise-grade customers.

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Lead the engineering team responsible for the Reporting product, owning the technical strategy, partnering with Product and Design to shape the roadmap, and ensuring the team has what they need to build, ship, and iterate with confidence. Build and lead a team of engineers and engineering managers by hiring exceptional people and developing them, own the technical architecture focusing on scalability, reliability, and long-term maintainability, and partner with Product, Design, and Clinical teams to translate complex customer needs into engineering solutions. Drive a culture of technical excellence by setting high standards for code quality, system design, and engineering practices while balancing shipping priorities. Serve as a key voice in company-wide engineering strategy, representing the Reporting team at the leadership level. Engage directly in technical and leadership work, setting technical standards, modeling culture, and supporting the team through challenges and high-stakes situations.