AI Engineer

AI Engineer

The role involves building customer-facing features from scratch using strong frontend skills while integrating and scaling the underlying AI infrastructure. This includes owning features end-to-end, crafting reliable software, and applying applied AI knowledge beyond the API layer to ensure system reliability.

Senior DevOps Engineer, AI Platform

You will design, provision, and operate scalable production infrastructure for AI platforms, web applications, and backend services. This includes managing Kubernetes environments, CI/CD pipelines, and implementing end-to-end observability to ensure system reliability and performance.

Product Engineer (AI / Full-Stack)

You will own product features end-to-end, from customer discovery and technical planning to production deployment and validation. You will work across the full stack to build agent-first research tools while collaborating directly with founders and the engineering team.

Applied AI Engineer

The Applied AI Engineer will design, build, and deploy AI-powered applications to solve business challenges and improve operational efficiency. They will collaborate with cross-functional teams to integrate AI solutions with enterprise data and systems while ensuring performance, scalability, and security.

Staff Product Security Engineer - AI Systems

You will define and build the security architecture for AI systems and the surrounding cloud platform, ensuring secure defaults and robust controls. This role involves hands-on engineering, adversarial testing, and embedding security practices directly into the development lifecycle.

Backend AI Engineer

Design and maintain backend services and AI infrastructure to support model-serving pipelines and enterprise integrations. Collaborate with cross-functional teams to translate technical requirements into scalable, production-grade systems.

Senior Software Engineer, AI

Lead Backend Engineer, AI Platform

The Lead Backend Engineer will design and maintain high-performance distributed systems and AI-powered backend capabilities. They are responsible for providing technical leadership, mentoring engineers, and collaborating with cross-functional teams to deliver scalable and secure solutions.

Lang Chain Deployment AI Engineer

Translate approved AI architectures into secure, scalable, and production-ready applications using LangChain and LangGraph. Build and deploy LLM-powered assistants, RAG pipelines, and agentic workflows while ensuring operational readiness and performance.

Staff Software Engineer – AI & Platform (Freelance)

You will define technical strategy for platform architecture and AI-enabled engineering while leading cross-functional initiatives. Additionally, you will contribute to the reliability and scalability of a high-traffic consumer platform through hands-on implementation and technical coaching.

Backend Engineer, AI Engineering: Duo Chat

Develop and maintain agentic flows for GitLab Duo Chat using Python, LangGraph, and the Duo Workflow Service. Integrate chat capabilities with the GitLab Rails monolith and collaborate with cross-functional teams to ensure high-scale performance and security.

Staff AI Engineer

The Staff AI Engineer will design, build, and ship production-grade agentic AI workflows using tools like LangGraph and Temporal. They will also own AI observability, set engineering standards, and mentor team members to enhance AI capabilities.

Senior Software Engineer, AI

Design, build, and deploy production-grade AI systems, including autonomous agents and LLM-powered applications. Manage end-to-end data pipelines, model evaluation, and performance optimization to ensure scalable and secure business solutions.

Senior AI Engineer, Legal - USA Remote

The Senior Legal Engineer designs, builds, and deploys AI-powered solutions to automate and transform legal and compliance workflows. This role involves partnering with legal stakeholders to architect scalable applications using LLMs, RAG, and agentic AI frameworks.

Senior Software Engineer (AI & Full Stack)

Senior AI Engineer

The AI Engineer will design and implement advanced AI models that integrate with MS Dynamics and Azure platforms to improve organizational efficiency. They will also collaborate with cross-functional teams to maintain scalable AI solutions and provide technical guidance to stakeholders.

Advanced Analytics / AI Engineer

The Advanced Analytics / AI Engineer will design and implement analytics solutions using MS Dynamics and Azure to support business objectives. They will also develop machine learning models and collaborate with cross-functional teams to derive actionable insights from complex datasets.

Applied AI Engineer, Agents & Automations

You will build and improve AI-powered product experiences by designing interfaces for human-AI collaboration and implementing robust eval and feedback systems. You will work cross-functionally to ensure AI reliability through prompt engineering, context construction, and data-driven product improvements.

Applied AI Engineer

You will build and ship LLM-powered features and agentic workflows within a complex financial platform. You will also own the data engineering layer to ensure high-quality data pipelines and retrieval architectures for AI systems.

Staff Agentic AI Engineer

You will design and build production-grade agentic AI systems and architect complex workflows involving reasoning, tool use, and retrieval. Additionally, you will develop evaluation systems for LLMs and partner with cross-functional teams to translate AI capabilities into reliable platform features.

Staff Firmware Engineer, AI Native, Edge ML

You will design and build a reusable on-device inference framework to enable edge machine learning across the company's hardware portfolio. Additionally, you will perform core firmware engineering tasks, including driver development and debugging, while integrating ML models into resource-constrained environments.

Lead AI Engineer- GTM Systems

Define and own the technical vision for AI-powered Go-To-Market systems, including both low-code automation and custom agentic AI pipelines. Lead architectural design for complex, enterprise-scale workflows while establishing standards and reference architectures for the engineering team.

Security Engineer, AI Security

The Security Engineer will design security controls and validate AI/ML services and applications throughout the full secure development life-cycle. Responsibilities include conducting security reviews, leading penetration testing, developing security automation, and providing mentorship to team members.

Senior Software Engineer, AI Platform (US - Remote or Calgary)

You will own the core runtime surfaces of the AI platform, including agent loops, tool execution, and memory management. Additionally, you will collaborate with product teams to integrate domain content and ensure the reliability and observability of the platform in production.

Forward Deployment Engineer, AI - Canada Remote

The Forward Deployment Engineer will manage the deployment of AI voice agents to new customers while optimizing core product features and performance. This role involves building evaluation suites, monitoring production systems, and collaborating with cross-functional teams to streamline the customer onboarding process.

Forward Deployed Engineer (AI Capability Center) - 5 Openings

The engineer will build features and solutions within a pod, working directly with business users to implement AI-driven applications. They are responsible for maintaining high code quality through testing and evaluations while following design direction from the Solution Architect.

Senior Frontend Software Engineer (AI Receptionist)

You will design and build modern, responsive web applications to power AI Receptionist experiences for enterprise customers. This involves collaborating with cross-functional teams to integrate frontend applications with backend services and AI-powered capabilities.

Gen AI Engineer

Software Engineer, AI Enablement

The role focuses on building tools, workflows, and practices to help Tailscale's engineering organization effectively adopt AI-assisted development. This includes evaluating AI models, developing security guardrails for AI-generated code, and acting as an internal advocate for AI productivity.