Ai Systems Engineer Jobs

About Scale AI Scale AI is the data foundation for AI, helping organizations build and deploy reliable production AI applications. We partner with the world's leading enterprises and government organizations to accelerate their AI transformation through frontier AI systems that solve real business problems. Every day, we work with organizations across finance, healthcare, manufacturing, media and telecommunications to build production AI agents that automate complex workflows, help humans, reason over enterprise knowledge, and operate safely at scale. The Opportunity Applied AI is moving faster than ever. New foundation models, reasoning techniques, agent architectures, and research papers emerge every week. Yet building AI systems that reliably solve real-world problems remains one of the hardest engineering challenges. As a Senior Frontier Agent Engineer (Applied AI) , you'll bridge the gap between cutting-edge AI research and production deployment. You'll work directly with enterprise customers to design, evaluate, and deploy intelligent systems that combine frontier models with structured knowledge, retrieval, traditional machine learning, and enterprise software. Unlike traditional ML roles that focus on a single model or product, you'll work across a diverse portfolio of AI challenges spanning multiple industries and use cases. You may build a multi-agent research system and then participate in designing a customer intelligence platform, a healthcare copilot, or an autonomous workflow for a Fortune 100 company. If you enjoy reading new AI papers, experimenting with the latest models, and shipping production systems that create measurable business impact, you'll fit right in. What You'll Build Frontier AI Systems Design and deploy production AI agents that leverage the latest advances in large language models, reasoning, retrieval, memory, and tool use. Architect intelligent systems that combine LLMs, traditional machine learning, structured knowledge, enterpri

About the Team The Merchant (Mx) AI/ML team is a cornerstone of DoorDash’s merchant organization. We empower our restaurant partners to thrive on DoorDash by building intelligent, scalable AI systems that simplify operations, elevate their digital presence, and enhance customer engagement. Our world-class machine learning engineers develop production-grade AI solutions that power the entire merchant lifecycle — from onboarding and store setup to menu management, growth, and real-time order operations. The team is deeply customer-obsessed and impact-driven, focused on turning cutting-edge research in LLMs, multimodal learning, generative AI, and agentic automation into products that make our merchants more successful every day. About the Role We’re looking for an Engineering Manager to lead the Mx AI/ML team, driving the design and deployment of next-generation AI product solutions that power our merchant experiences. This is a highly cross-functional leadership role — you’ll collaborate with product, design, operations, and data science teams to define the AI roadmap, guide technical direction, and deliver end-to-end AI/ML solutions at massive scale. You’ll lead a team of talented ML engineers who are building real AI products delivered to merchants’ fingertips, helping them become more successful on DoorDash. You’re excited about this opportunity because you will… Lead and grow a team of exceptional AI/ML engineers developing production-grade machine learning and generative AI solutions for the merchant ecosystem. Define a multi-year strategy and execute the AI roadmap across key Mx pillars — Onboarding, Menu Media Understanding & Generation, Menu Metadata Intelligence, and Agentic Task Automation. Partner with product and operations to translate merchant pain points into scalable AI-powered solutions. Own the end-to-end lifecycle of ML systems — from ideation and experimentation to productionization and continuous improvement. Drive innovation in multimodal AI

Research Engineer, Applied AI Location: Bangalore (or throughout India remote-friendly with travel) About EnCharge AI: EnCharge AI is building the next generation AI platform. Our novel in-memory-computing architecture delivers a 10x step-function improvement in compute energy efficiency and performance for AI inference workloads. As the demands of artificial intelligence move beyond today's models, we believe fundamental underlying infrastructure must evolve. We are an experienced team of AI researchers, silicon & systems engineers, and architects backed by leading investors, poised to become the essential platform for the next wave of AI innovation. The Opportunity: Modern AI workloads—from large language models to diffusion-based generators to multimodal systems—represent some of the most compute-intensive frontiers in AI, and some of the most promising applications for our hardware’s energy efficiency advantages. We’re building a vertically integrated AI stack that will showcase the transformative potential of our silicon while delivering real value to customers today. We are seeking a Research Engineer to push the boundaries of AI model capability, quality, and efficiency. You’ll build fine-tuning and post training pipelines, develop rigorous benchmarking frameworks, and work at the intersection of ML research and hardware-aware optimization—ensuring our models run beautifully on our silicon. This is a role for someone who thrives at the boundary between research and engineering. You’ll read papers, implement techniques, and ship production-quality code—all in service of making AI inference faster, cheaper, and better. Key Responsibilities: Algorithmic Acceleration: Research and implement state-of-the-art techniques to accelerate AI inference—quantization, sparsity,

Become a part of our caring community You have shipped AI products before. You understand the difference between a demo and a production system. You have strong opinions about evaluation frameworks because you have experienced the consequences of operating without them. You are at your best when you own architecture decisions while continuing to build and deliver critical code yourself. We build the platform that transforms millions of clinical documents into trusted, actionable data. Our systems use large language models (LLMs) to read medical records, extract structured facts, answer complex questions with citations back to source documents, and route complex cases to human experts. The output of these systems supports healthcare decisions that impact real members. As a Lead AI Applied Engineer, you will provide technical leadership for AI-enabled products and platforms, define architectural direction, establish engineering standards, and personally design and build the most critical components of our systems. You will lead through both technical expertise and execution, helping the team deliver reliable, scalable, and auditable AI solutions in a highly regulated healthcare environment. Why Join Us Lead the architecture of production AI systems where LLMs are foundational to the product experience. Make key technical decisions regarding model selection, system boundaries, platform architecture, and build-versus-buy strategies. Own the highest-risk and highest-impact technical challenges involving reliability, explainability, and correctness. Influence engineering culture and establish standards that shape how the team builds and ships AI products. Work on systems operating at meaningful scale, processing millions of documents and supporting healthcare decisions across a large member population. Partner

About the Team The Applied AI Engineering team is responsible for helping developers and enterprises safely and effectively deploy OpenAI technologies in production. We act as trusted technical advisors and thought partners for customers, working side by side with their teams to identify high-value use cases, design practical architectures, and move from prototype to durable deployment. Cybersecurity is one of the most urgent domains where AI can help. Security teams are under pressure to reason across code, logs, infrastructure, tickets, alerts, and vulnerability data faster than ever. As frontier models become more capable, organizations need deep technical guidance on how to evaluate, validate, and safely deploy AI systems in security-critical workflows. About the Role We are looking for a Cybersecurity Applied AI Engineer to partner with customers and help them apply OpenAI models, APIs, Codex, and agentic workflows to real cybersecurity use cases. You will work with CISOs, security executives, application security leaders, SOC teams, security engineering teams, and hands-on practitioners to identify where AI can create measurable security outcomes. This is a customer-facing technical role for someone who can move fluidly between executive strategy, practitioner-level cyber depth, and hands-on solution design. You will help customers evaluate and deploy workflows such as secure code review, vulnerability triage, threat modeling, remediation, SOC and incident response workflows, detection engineering, cloud security, GRC automation, and security validation. You will collaborate closely with Sales, Solutions Engineering, Product, Engineering, Research, and Security to turn customer needs into safe deployment patterns, reusable field assets, and product feedback. This role is based in our Dublin Office. We offer relocation support to new employees. In this role, you will: Deeply embed with strategic customers as the technical lead for AI-enabled cybersecurity workf

About the Team The Applied AI Engineering team is responsible for helping developers and enterprises safely and effectively deploy OpenAI technologies in production. We act as trusted technical advisors and thought partners for customers, working side by side with their teams to identify high-value use cases, design practical architectures, and move from prototype to durable deployment. Cybersecurity is one of the most urgent domains where AI can help. Security teams are under pressure to reason across code, logs, infrastructure, tickets, alerts, and vulnerability data faster than ever. As frontier models become more capable, organizations need deep technical guidance on how to evaluate, validate, and safely deploy AI systems in security-critical workflows. About the Role We are looking for a Cybersecurity Applied AI Engineer to partner with customers and help them apply OpenAI models, APIs, Codex, and agentic workflows to real cybersecurity use cases. You will work with CISOs, security executives, application security leaders, SOC teams, security engineering teams, and hands-on practitioners to identify where AI can create measurable security outcomes. This is a customer-facing technical role for someone who can move fluidly between executive strategy, practitioner-level cyber depth, and hands-on solution design. You will help customers evaluate and deploy workflows such as secure code review, vulnerability triage, threat modeling, remediation, SOC and incident response workflows, detection engineering, cloud security, GRC automation, and security validation. You will collaborate closely with Sales, Solutions Engineering, Product, Engineering, Research, and Security to turn customer needs into safe deployment patterns, reusable field assets, and product feedback. This role is based in our Tokyo office. We offer relocation support to new employees. In this role, you will: Deeply embed with strategic customers as the technical lead for AI-enabled cybersecurity workfl

About the Team The Applied AI Engineering team is responsible for helping developers and enterprises safely and effectively deploy OpenAI technologies in production. We act as trusted technical advisors and thought partners for customers, working side by side with their teams to identify high-value use cases, design practical architectures, and move from prototype to durable deployment. Cybersecurity is one of the most urgent domains where AI can help. Security teams are under pressure to reason across code, logs, infrastructure, tickets, alerts, and vulnerability data faster than ever. As frontier models become more capable, organizations need deep technical guidance on how to evaluate, validate, and safely deploy AI systems in security-critical workflows. About the Role We are looking for an Applied AI Engineer, Cyber to partner with customers and help them apply OpenAI models, APIs, Codex, and agentic workflows to real cybersecurity use cases. You will work with CISOs, security executives, application security leaders, SOC teams, security engineering teams, and hands-on practitioners to identify where AI can create measurable security outcomes. This is a customer-facing technical role for someone who can move fluidly between executive strategy, practitioner-level cyber depth, and hands-on solution design. You will help customers evaluate and deploy workflows such as secure code review, vulnerability triage, threat modeling, remediation, SOC and incident response workflows, detection engineering, cloud security, GRC automation, and security validation. You will collaborate closely with Sales, Solutions Engineering, Product, Engineering, Research, and Security to turn customer needs into safe deployment patterns, reusable field assets, and product feedback. This role is based in our Singapore office. We offer relocation support to new employees. In this role, you will: Deeply embed with strategic customers as the technical lead for AI-enabled cybersecurity workflow

Biohub is the first large-scale initiative bringing frontier AI models, massive compute, and frontier experimental capabilities under one roof. We're building a general-purpose system to accelerate scientific discovery, integrating frontier AI models, biological foundation models, and lab capabilities, with the ultimate goal of curing disease. Our technology powers scientists around the world, translating AI capabilities into tools that accelerate research everywhere. The Team The AI Cluster Production Engineering team is part of the AI Compute Platform organization at Biohub, a non-profit research lab committed to open science and open-source AI. We own the design, operation, and reliability of large-scale multi-GPU AI clusters that power frontier AI biology research: protein language models, genomic foundation models, and scientific reasoning systems built to be shared, not monetized. Our clusters run Slurm on Kubernetes infrastructure and support everything from day-to-day AI researcher workflows to multi-node hero training runs at thousands of GPUs. The team works at the intersection of AI tooling, distributed systems, HPC, and frontier AI, debugging deep AI infrastructure problems and building AI systems critical to the entire AI organization. The Opportunity CZ Biohub's mission is to cure or prevent all human disease. Achieving that requires training frontier-scale AI biology models, and that demands reliable, high-performance compute infrastructure. This is production engineering work at a frontier AI lab, with the twist that the mission is biology and the science is open. You'll keep GPU clusters running at high utilization, debug the toughest distributed systems failures, and build the operational foundations for scaling to multi-thousand GPU hero runs. The technical problems are genuinely hard (e.g., multi-node distributed training, InfiniBand fabrics, large-scale storage, Slurm at scale) inside an organization where the work is aimed at helping peop

About the Role We're looking for a Senior AI Engineer to help advance Amplitude's AI products and the foundations they're built on. As AI reshapes how customers analyze data, build products, and act on insights, we need engineers who can move fluidly between deep technical work and product judgment, shipping AI capabilities that customers and internal teams actually rely on. This role is both visionary and hands-on. You'll identify where AI creates the most leverage, build the systems that deliver it, and establish the patterns that let the rest of the company build faster on top of your work. You'll contribute to customer-facing AI products, the platform infrastructure beneath them, and the internal tooling that helps Amplitude operate as an AI-native company. What You'll Do Ship high-impact AI features and products that change how customers and internal teams work, from agentic workflows to embedded intelligence across the Amplitude platform Design and build the foundational infrastructure behind Amplitude's AI systems: orchestration, evaluation, retrieval, context management, and integrations with the broader product ecosystem Identify high-leverage opportunities by deeply understanding user workflows, customer pain points, and emerging capabilities in the AI ecosystem Establish reusable patterns, primitives, and components that enable other engineers to build AI features confidently and consistently Drive adoption and quality through close collaboration with product, design, and customer-facing teams, with a relentless focus on real usage and measurable outcomes Set technical direction for AI systems at Amplitude, making thoughtful build vs. buy calls, shaping evaluation strategy, and influencing the long-term roadmap Who You Are You're a highly capable engineer with a strong track record of shipping AI-powered systems that people actually use. You bring deep technical instincts, strong product sense, and a forward-thinking view of where AI is heading. Experienc

Who are we? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! Why this role? North is Cohere's cutting-edge AI workspace platform, designed to revolutionize the way enterprises utilize AI. It offers a secure and customizable environment, allowing companies to deploy AI while maintaining control over sensitive data. North integrates seamlessly with existing workflows, providing a trusted platform that connects AI agents with workplace tools and applications. Some of our most important work is making the agents and AI-powered experiences inside North genuinely useful in the workflows customers rely on every day. These systems become valuable when users can build with them, steer them, inspect their work, recover from errors, and trust them to complete messy tasks inside real enterprise environments. This role is about making those AI experiences reliable, useful, and production-ready. You’ll work with product engineering, modelling and design to turn model capability into reliable, user-facing systems: agent builders, eval frameworks, proactive intelligence, and new interfaces for collaborating with AI. Sometimes that means shipping a new product surface, sometimes a better eval or feedback

At ClickUp, we're building the future of work: the first truly converged AI workspace unifying tasks, docs, chat, calendar, and enterprise search, all supercharged by context-driven AI. We are an AI-native company. Every team member is expected to leverage AI daily, and we evaluate AI fluency as part of our hiring process. Join us and help redefine what's possible. 🚀 Role Overview: We are seeking a highly skilled Staff AI Engineer - Multi-Agent Frameworks to join our AI Platform team. In this role, you will play a pivotal part in building a cutting-edge platform that empowers our users to create and deploy sophisticated intelligent agents, with a key focus on enabling collaborative and multi-agentic behaviors . This is a backend-focused role that requires deep expertise in AI, large language models (LLMs), and orchestration software. Key Responsibilities: Design, develop, and maintain a robust platform to enable users to create and manage AI agents and their interactions. Integrate and work with multiple LLMs, ensuring seamless orchestration and scalability for both individual and coordinated agent operations. Leverage orchestration frameworks like LangGraph and others to build complex workflows and pipelines that support diverse agent functionalities, including frameworks for multi-agent coordination . Develop and implement evaluation frameworks for testing AI agents in challenging and complex scenarios, focusing on individual performance and system-level dynamics. Stay at the forefront of AI advancements, incorporating the latest research and technologies into our platform to enhance agent capabilities and collaboration. Collaborate with cross-functional teams, including product managers, designers, and frontend engineers, to deliver a seamless user experience for building and deploying intelligent systems. Address challenging AI privacy scenarios, ensuring compliance with data protection regulations and best practices within agent-based applications. Contribute

At ClickUp, we're building the future of work: the first truly converged AI workspace unifying tasks, docs, chat, calendar, and enterprise search, all supercharged by context-driven AI. We are an AI-native company. Every team member is expected to leverage AI daily, and we evaluate AI fluency as part of our hiring process. Join us and help redefine what's possible. 🚀 Role Overview: We are seeking a skilled and experienced Senior AI Engineer - Multi-Agent Frameworks to join our AI Platform team. In this role, you will play a pivotal part in building a cutting-edge platform that empowers our users to create and deploy sophisticated intelligent agents, with a key focus on enabling collaborative and multi-agentic behaviors . This is a backend-focused role that requires deep expertise in AI, large language models (LLMs), and orchestration software. Key Responsibilities: Design, develop, and maintain a robust platform to enable users to create and manage AI agents and their interactions. Integrate and work with multiple LLMs, ensuring seamless orchestration and scalability for both individual and coordinated agent operations. Leverage orchestration frameworks like LangGraph and others to build complex workflows and pipelines that support diverse agent functionalities, including frameworks for multi-agent coordination . Develop and implement evaluation frameworks for testing AI agents in challenging and complex scenarios, focusing on individual performance and system-level dynamics. Stay at the forefront of AI advancements, incorporating the latest research and technologies into our platform to enhance agent capabilities and collaboration. Collaborate with cross-functional teams, including product managers, designers, and frontend engineers, to deliver a seamless user experience for building and deploying intelligent systems. Address challenging AI privacy scenarios, ensuring compliance with data protection regulations and best practices within agent-based applications. C

At ClickUp, we're building the future of work: the first truly converged AI workspace unifying tasks, docs, chat, calendar, and enterprise search, all supercharged by context-driven AI. We are an AI-native company. Every team member is expected to leverage AI daily, and we evaluate AI fluency as part of our hiring process. Join us and help redefine what's possible. 🚀 Role Overview You'll own and evolve the AI systems behind ClickUp's voice platform: real-time streaming transcription, intelligent reformatting, context-aware mention detection, and voice-to-action pipelines. This is a high-impact, hands-on role where you'll push the boundaries of what voice interfaces can do inside a productivity tool used by millions. Key Responsibilities Design, build, and optimize real-time speech-to-text pipelines (streaming ASR, VAD, audio processing) Improve transcription accuracy through context injection (user names, teams, custom vocabulary, language detection) Develop and maintain LLM-powered post-processing (grammar correction, filler removal, mention resolution, formatting) Build voice-to-action systems that parse natural language into structured workspace commands Evaluate, benchmark, and integrate ASR models (Whisper, AssemblyAI, Fireworks, etc.) for cost, latency, and accuracy Collaborate with product and platform teams to ship voice features across MAX Desktop, Mobile, Web, and Browser Extension Explore multimodal AI capabilities (screen + voice + text) for next-gen assistant experiences Equal Opportunity Employer ClickUp is an Equal Opportunity Employer, and qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, or national origin. Privacy Notice ClickUp collects and processes personal data in accordance with applicable data protection laws. You can find further details by viewing our Global Candidate Privacy Notice. If you are a Philippine Job Applicant, please also see our Phi

We believe that the way people interact with their finances will drastically improve in the next few years. We’re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid’s network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Washington D.C., London and Amsterdam. Team Description: Plaid is evolving into an AI-first company, and Intelligent Tooling sits at the center of that transformation. The Intelligent Tooling team is being built from the ground up, and our mission is to establish the technical foundations, operating model, and internal platforms that embed AI deeply into Plaid’s coding tools, internal systems, and the entire software development lifecycle. When we are successful, engineers across Plaid will delegate lower-leverage work to AI agents, move faster with confidence, and spend more of their time designing and inventing for customers. Intelligent Tooling owns the platforms and systems that make this possible - from AI coding integrations and SDLC agents to the internal tools that power Plaid’s operations. Role Description: As a Staff Software Engineer on the Intelligent Tooling team, you will build and operate internal systems that directly impact how engineers across Plaid do their work, and own the technical direction for major parts of that surface. This is a hands-on role with significant ownership, where success is measured by real adoption, reliability, and improvements to developer experience. You will work on AI-powered tooling, interna

Ready to do the most impactful work of your career? At Coinbase , we are uncompromising on our mission to increase economic freedom. The bar is high, the environment is intense, and we like it that way. This isn't a place for complacency, it’s a place to be pushed past your perceived limits. If you're ready to build the future of finance alongside people who refuse to settle for "good enough," you belong here. Coinbase is a remote-first, but not remote-only company. Expect to get together quarterly for intense in-person working sessions called “surges.” learn more about working at Coinbase . As a Senior Software Engineer on the Platform Core Automation team, you'll build the AI infrastructure and agentic systems that automate customer support and compliance operations at Coinbase. This team is reimagining what these processes look like when AI handles them end-to-end, replacing manual workflows with intelligent agents that resolve customer issues and execute compliance tasks autonomously. You'll own the design and delivery of LLM-powered systems, grounding techniques, and integration pipelines that directly reduce resolution times, cut costs, and improve accuracy across millions of customer interactions. What you’ll be doing (ie. job duties): Own the design and delivery of agentic AI systems that power Coinbase's customer support and compliance automation, from LLM orchestration through production deployment and monitoring. Build scalable, secure backend infrastructure in Python and Golang that serves AI workloads, including model integration pipelines, guardrails, grounding mechanisms, and measurement frameworks. Drive end-to-end project execution on complex AI initiatives, making technical trade-offs across latency, accuracy, cost, and reliability. Partner with Customer Experience, Compliance, and product engineering teams to identify high-impact automation opportunities and translate operational pain points into AI-powered solutions. Strengthen engine