TypeScript AI Jobs

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The Forward Deployed Engineer Lead is responsible for partnering with Deployment Strategists and Sales to understand enterprise customer needs, architecting solutions, and developing transformative agentic applications. They architect and build complex agentic systems using state-of-the-art models, orchestrate sophisticated LLM workflows, and integrate deeply with enterprise infrastructure. The role involves collaborating with research teams to adapt and fine-tune models for customer-specific needs and contributing to the internal codebase for inference, fine-tuning, and evaluation. They own end-to-end deployments across hybrid environments including public cloud, VPC, and on-premises, ensuring production-grade scalability, performance, and reliability. Additionally, they shape and scale the Forward Deployed Engineering organization by defining playbooks, best practices, technical standards, and providing mentorship to support team growth.

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As a Forward Deployed Engineer on Reflection's Applied AI team, you will partner with Deployment Strategists and Sales to understand enterprise customer needs, architect solutions, and develop transformative agentic applications. You will build agentic systems using state-of-the-art models, orchestrate LLM workflows, integrate with enterprise infrastructure, and deploy reliable production systems. You will collaborate with research teams to adapt and fine-tune models for customer-specific needs. You will support end-to-end deployments across hybrid environments, including public cloud, VPC, and on-premises, ensuring scalability, performance, and reliability in production. You will also contribute to evolving playbooks, processes, and best practices as part of a growing Forward Deployed Engineering organization.

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As a Senior Applied AI Engineer at Vanta, you will work cross-functionally to design and implement AI-powered features that deliver customer value and integrate large language models (LLMs) with Vanta's existing products and systems. You will collaborate with product engineers across Vanta to understand how AI systems can accelerate product adoption, instrument evaluations, guardrails, and monitoring, and review customer usage to continually improve quality. Additionally, you will collaborate with AI Platform engineers on foundational AI systems and tooling to accelerate product teams, make pragmatic tradeoffs considering business priorities, user experience, and sustainable technical foundation, mentor engineers, champion good technical and product instincts, and model a collaborative, high-ownership engineering culture.

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As a Forward Deployed Engineer Lead, you will own the end-to-end technical strategy, execution, and delivery of complex agentic applications, from early pre-sales discovery through production deployment. Responsibilities include partnering with Deployment Strategists and Sales to understand enterprise customer needs, architecting solutions, and developing transformative agentic applications. You will architect and build complex agentic systems using state-of-the-art models, orchestrate sophisticated LLM workflows, and integrate deeply with enterprise infrastructure. Collaboration with research teams to adapt and fine-tune models for customer-specific needs and contributing to the internal codebase for inference, fine-tuning, and evaluation is required. You will own end-to-end deployments across hybrid environments including public cloud, VPC, and on-premises, ensuring production-grade scalability, performance, and reliability. Additionally, you will shape and scale the Forward Deployed Engineering organization by defining playbooks, best practices, technical standards, and providing mentorship to support team growth.

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As a Forward Deployed Engineer at Reflection, you will partner with Deployment Strategists and Sales to understand enterprise customer needs, architect solutions, and develop transformative agentic applications. You will build agentic systems using state-of-the-art models, orchestrate LLM workflows, integrate with enterprise infrastructure, and deploy reliable production systems. You will collaborate with research teams to adapt and fine-tune models for customer-specific needs. You will support end-to-end deployments across hybrid environments such as public cloud, VPC, and on-premises, ensuring scalability, performance, and reliability in production. Additionally, you will contribute to evolving playbooks, processes, and best practices as part of the growing Forward Deployed Engineering organization.

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Build and scale reinforcement learning environments and platforms behind them; drive architecture for scalable, reliable, extensible environment systems and data generation pipelines; partner with Research, Product, and Ops teams to turn ambiguous needs into production systems; build modular, plug-and-play domains that integrate cleanly with training and evaluation loops; improve reliability, observability, performance, and data quality of systems.

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Lead, mentor, and grow a team of AI Deployment Engineers supporting strategic AWS partner engagements and customer deployments. Define the operating model, engagement strategy, and technical priorities for the AWS Partner ADE pod. Partner closely with AWS partner leadership, solution architects, delivery organizations, and customer stakeholders to accelerate production adoption of OpenAI technologies. Guide teams through complex generative AI and traditional ML deployments, including architecture reviews, implementation planning, security considerations, evaluation strategies, and operational readiness. Serve as a senior technical escalation point for critical partner and customer engagements. Collaborate with Product, Research, and Engineering teams to synthesize partner feedback into platform improvements, tooling enhancements, and deployment best practices. Develop scalable enablement frameworks, reference architectures, and repeatable deployment patterns to improve partner effectiveness and reduce time-to-production. Drive operational excellence including resource planning, prioritization, hiring, onboarding, performance management, and career development. Act as an external thought leader on enterprise AI deployment, cloud-native AI architectures, and responsible AI adoption within the AWS ecosystem.

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As a Senior Backend & AI Engineer, the responsibilities include designing, developing, deploying, and operating business-critical AI features. The role involves collaborating on requirements analysis to design technical and business solutions, proposing innovative solutions by staying ahead of AI trends and technologies, owning key responsibilities in the design, architecture, and end-to-end delivery of AI-driven modules, and writing clean, scalable, and maintainable code with proper testing, deployment, and monitoring. Additional duties include continuously improving code quality by refactoring, debugging, and enhancing performance, contributing to building secure, high-quality AI solutions for customer experience, optimizing product and platform performance with live site monitoring, and participating in an on-call rotation to handle critical incidents and maintain system uptime.

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Design and develop robust, secure, and scalable generative AI services and applications using Python and modern frameworks to drive enterprise-wide transformation; build and optimize high-performance, low-latency APIs and microservices to integrate advanced AI models and sophisticated agentic workflows into the core platform; make meaningful system design decisions and own the architecture of core platform components from initial proposal through production deployment; implement and maintain responsive user interfaces using technologies like React and TypeScript; clearly communicate changes, plans, and proposals to cross-functional teams and collaborate with product managers, data scientists, and DevOps engineers; partner with DevOps teams to build continuous deployment, logging, and monitoring systems to ensure top-tier performance, security, and reliability across distributed workloads.

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Design and develop robust, secure, and scalable generative AI services and applications using Python and modern frameworks to drive enterprise-wide transformation. Build and optimize high-performance, low-latency APIs and microservices to integrate advanced AI models and sophisticated agentic workflows into the core platform. Make meaningful system design decisions and own the architecture of core platform components from initial proposal through production deployment. Implement and maintain responsive user interfaces using technologies like React and TypeScript to deliver intuitive user experiences and bridge the gap between backend services and frontend enablement. Communicate changes, plans, and proposals clearly to cross-functional teams and collaborate closely with product managers, data scientists, and DevOps engineers. Partner with DevOps teams to build continuous deployment, logging, and monitoring systems that ensure top-tier performance, security, and reliability across distributed workloads.