TypeScript AI Jobs

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As a Principal Software Architect at HackerOne, you will define and evolve the architectural vision for the HackerOne Platform and core systems to ensure scalability, reliability, and performance. You will partner with Product, Platform, and Security teams to translate long-term business and product goals into actionable architectural strategies. You will collaborate with Principal and Distinguished Engineers to align on technical direction, establish shared standards, and evolve system design principles. Your role involves leading major cross-team initiatives to modernize architecture, improve observability, and reduce complexity. You will mentor and guide engineering teams to foster technical excellence, knowledge sharing, and continuous improvement. You will evaluate and integrate emerging technologies including AI, GenAI, and LLM-driven architectures to enhance platform intelligence. Additionally, you will drive architectural governance and documentation to ensure maintainability and transparency and communicate architectural direction clearly to technical and non-technical stakeholders. Within the first 30-90 days, you will move from understanding systems and architecture to leading architectural initiatives that impact teams company-wide.

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You will be building a new team in the US to develop the next generation smart AI video maker that can ingest user's content and compose quality videos for social media. You will work closely with product and marketing teams to quickly prototype, beta test, and produce the final version of this product using agent technology. The technology stack includes GCP, Typescript, Python, Redis, MongoDB, Cloud Storage, and various AI models. You will be involved in rushing prototype and production versions of this product, contributing to an innovative and ambitious project.

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As an AI Engineer (New Graduate) at Distyl, you will design, implement, and deploy GenAI applications under the guidance of senior engineers, contributing to prompt design, agent logic, retrieval-augmented generation (RAG), and model evaluation to build full-stack AI applications that deliver measurable business value. You will gain exposure to customer-facing work by shadowing technical conversations and learning how business needs are translated into system design, with opportunities to take on more responsibility in technical decisions and implementation. You will partner with senior engineers to understand customer problems and translate requirements into technical solutions, participate in customer discussions, solution design sessions, and iterative delivery. Additionally, you will help improve Distillery, Distyl’s internal LLM application platform, by building reusable components, tools, and workflows and learn best practices for scalable, maintainable AI infrastructure. You will write clean, well-tested, observable production-quality code that meets reliability, performance, and security standards and learn how production AI systems are monitored, debugged, and improved over time. You will assist with evaluating AI systems across accuracy, latency, cost, and robustness, applying user feedback and metrics to improve system performance. Finally, you will continuously develop your skills in LLMs, software engineering, and AI through mentorship, code reviews, and hands-on project work, learning modern development workflows and deployment practices used in enterprise AI.

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As a Full-Stack Software Engineer on the Security Products team, you will build, deploy, and maintain applications and systems that bring advanced AI-driven security capabilities to real users. You will work directly with internal and external customers to understand their workflows and translate them into intuitive, powerful product experiences. Your responsibilities include designing and building efficient and reusable frontend systems that support complex web applications, planning and deploying frontend infrastructure necessary for building, testing, and deploying products, collaborating across OpenAI’s product, research, engineering, and security organizations to maximize impact, and helping to shape the engineering culture, architecture, and processes of this new business unit.

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As a Forward Deployed Engineer, you will be the driving force behind customer deployments, taking AI solutions from early concept and pilot to production launch with enterprise-grade reliability. You will translate cutting-edge AI capabilities into practical, high-performance systems tailored to real-world customer needs, designing and implementing agentic voice AI solutions that integrate seamlessly into customer workflows and infrastructure. Your role involves prototyping, iterating, and deploying AI-driven systems in close collaboration with enterprise customers, working closely with customers to define success criteria and ensure they achieve meaningful outcomes on Cartesia's platform. You will have significant autonomy to shape customer solutions and directly impact how cutting-edge AI is deployed at scale across global organizations.

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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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Develop AI agents and multi-agent systems by designing and implementing agents and extending existing agent capabilities, including managing the agent's context using techniques like sub-agents and retrieval-based context management. Develop complex tools for agents such as computer use and browser use. Research and build systems for multi-agent orchestration and agent tool calling to manage collaboration and tool usage. Engage in full-stack development to build and maintain production-grade APIs and AI-powered features, covering backend services to user-facing experiences. Evaluate AI performance using tests and evaluations to iterate and improve prompts, agent tools, and orchestration for better output quality and reliability.