Ai Agent Engineer Jobs

Secure Every Identity, from AI to Human Identity is the key to unlocking the potential of AI. Okta secures AI by building the trusted, neutral infrastructure that enables organizations to safely embrace this new era. This work requires a relentless drive to solve complex challenges with real-world stakes. We are looking for builders and owners who operate with speed and urgency and execute with excellence. This is an opportunity to do career-defining work. We're all in on this mission. If you are too, let's talk. The Staff AI Security Engineer Opportunity Identity is the key to unlocking the potential of AI. Okta secures AI by building the trusted, neutral infrastructure that enables organizations to safely embrace this new era. This work requires a relentless drive to solve complex challenges with real-world stakes. We are looking for builders and owners who operate with speed and urgency and execute with excellence. This is an opportunity to do career-defining work. We're all in on this mission. If you are too, let's talk. At Okta, we’re building the future of secure, enterprise-grade AI Agents. We’re looking for a Staff AI Security Engineer to join our dedicated Security team. In this role, you will define the technical vision, architecture, and hands-on security controls for AI models, agentic workflows, and autonomous systems across Okta. This is a senior individual contributor role for a hands-on engineer who can design scalable AI security infrastructure, mentor engineers, and partner with cross-functional teams to build secure "paved roads" for AI innovation. What you’ll be doing Secure AI Implementations: Design and deploy enterprise AI guardrails, gateways, and other controls to protect our agentic workflows from emerging threats Agent Hardening & Sandboxing: Establish security architectures for local and hosted agents to mitigate tool-calling, prompt injection, goal misalignment, and data exfiltration risks. Define Paved Roads & Secur

Secure Every Identity, from AI to Human Identity is the key to unlocking the potential of AI. Okta secures AI by building the trusted, neutral infrastructure that enables organizations to safely embrace this new era. This work requires a relentless drive to solve complex challenges with real-world stakes. We are looking for builders and owners who operate with speed and urgency and execute with excellence. This is an opportunity to do career-defining work. We're all in on this mission. If you are too, let's talk. Secure Every Identity, from AI to Human Identity is the key to unlocking the potential of AI. Okta secures AI by building the trusted, neutral infrastructure that enables organizations to safely embrace this new era. This work requires a relentless drive to solve complex challenges with real-world stakes. We are looking for builders and owners who operate with speed and urgency and execute with excellence. This is an opportunity to do career-defining work. We're all in on this mission. If you are too, let's talk. The AI-Core Team The team is building a scalable Agentic AI platform for agents that run real engineering work, agents that write code, triage incidents, investigate alerts, remediate vulnerabilities, upgrade libraries, patch flaky tests, automate runbooks, and other workloads across Okta's infra. Owning this platform means owning the hard cross cutting problems: agent identity, delegated access, secure isolated execution, orchestration, and governance, at the scale and reliability bar that Infra demands. The work is novel and high ownership, and the candidate should be drawn to problems the industry hasn't solved yet. What You'll Work On Design and implement backend APIs and services that make up the agentic platform Build the agent identity and machine-to-machine authentication system, including credential management and delegated access flows Build the agent knowledge base and memory layer so agents retain context within and across sessions Buil

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. The Cortex Apps team is building the future of AI for enterprise data. This role focuses on the backend infrastructure that powers our flagship products like Snowflake Intelligence , Cortex Agents and Search making agentic AI fast, reliable, scalable and secure at the enterprise level. You won’t just be using AI tools; you will be building the high-performance systems that orchestrate them. You’ll own and influence the architecture for agent execution environments, high-throughput context retrieval, or the ecosystem that allows our customers to iterate and launch agents in production. What you will do in this role: Architect Agentic Runtimes: Build and scale the orchestration engines that execute complex agentic workflows, ensuring low-latency tool execution and robust state management. Scale Context Engineering Infra: Design high-performance systems for RAG (Retrieval-Augmented Generation), including vector database integration, scalable and efficient search indexing, query processing, and result ranking, semantic caching, and automated metadata extraction. Build the "Evals Engine": Develop the automated infrastructure required to run massive-scale golden set simulations, error analysis pipelines, and "hillclimbing" experiments. Productionize AI Workflows: Collaborate with

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. About the AI Products team The AI Products team is part of the broader Marketplace & Collaboration organization and is focused on bringing AI products on top of Snowflake’s data and application platform to help customers discover, share, monetize, and act on data assets & applications more easily. This team is building the connective tissue of the agentic enterprise: the infrastructure and product surfaces that allow Snowflake customers to seamlessly share datasets, semantic views, and applications, and make them discoverable and executable through Cortex Code, CoWork, and other agentic harnesses. Our strategy is centered on evolving Snowflake Marketplace for the AI era, including packaging data and intelligence into ready-to-use agentic experiences, and enabling governed access patterns that let AI systems safely operate on enterprise data and applications. As a Staff Software Engineer on AI Products, you will Lead the design and delivery of large, complex initiatives spanning multiple teams, turning ambiguous product and platform opportunities into durable technical solutions. Shape the architecture for how datasets, applications, semantic assets, and agentic capabilities are shared, discovered, governed, and invoked across Snowflake surfaces and third-party agent

We're building the platform that lets long-running autonomous agents operate safely inside NVIDIA's enterprise. These are not assistants on a developer's laptop. They are fleets of agents deployed in the cloud, running continuously at scale on shared accelerated compute. They take on real work across enterprise systems, so people get far more done than they could before. This role defines the constructs that agents are built from: the blueprints they start from, the tools, skills, and plugins that power them against enterprise data, the runtime safety harness that keeps them in bounds, and the connections into credential management, sandbox, memory, and observability. The team designs and ships these building blocks so that agent developers across the company can stand up a new agent, wire it in, and run it for days or weeks. Security and safe execution come out of the box, not something each team has to get right on its own. Today an agent runs inside a single harness. Claude, Codex, and open-source agent harnesses each work differently underneath, with their own execution model, tool interface, and telemetry shape. The platform smooths over those differences, so a single skill, safety policy, or trace works the same no matter which harness is running. We want to enable agents that act on a person's behalf, governed and secure, continuously evaluated and self-improving. These agents coordinate and hand work off to each other, with identity and policy following every hop. They route and tune themselves across harnesses from live eval signals, and get better from their own production telemetry instead of waiting on a human to retrain them. Have you run agents on a harness like Claude or Codex and hit the walls that show up when they run for real, for days, against live systems — and wanted them to learn from it on their own? We're building the platform that solves those problems once, for every team. What you'll b

Build the infrastructure that keeps every NVIDIA chip aligned from first spec to final shipment. NVIDIA's Silicon Co-Design Group sits at the convergence of architecture, silicon, systems, and manufacturing. The System–Manufacturing Architecture (SMAC) team coordinates between system specifications and manufacturing test specifications from pre-silicon POR through production release across GPU, SoC, and CPU programs. When that alignment drifts, silicon faces the consequences: escapes, yield loss, and performance loss. We're hiring a Senior Manufacturing & System Co-Design Workflow Engineer to lead the methodology and infrastructure that maintains holistic, systematic alignment, at scale across the full portfolio. The strongest candidates in this role design the workflow before being asked to fix a program, and build the checks and automation that confirm alignment holds long after they've moved on to the next problem. What you’ll be doing: SMAC Workflow Methodology: Define manufacturing spec types, including schema and semantics, derived from system PORs and features. Own the methodology that governs how specification work gets structured, versioned, and validated across the program lifecycle. Production Python Pipelines & Automated Checks: Develop production-grade Python pipelines and automated checks that catch specification drift between system POR and manufacturing test programs ,ATE, SLT, BLT, L10+, before silicon exposes the discrepancy. The goal is that misalignments surface in the workflow, not on the tester. E2E Program Integration & TPM Attestation: Wire SMAC work into the end-to-end program spine, milestones, gates, and artifacts, and define explicit TPM-driven attestation when checks lag. Alignment can't be assumed; it must be proven at every stage. Agent-Ready Tooling & CI Infrastructure: Integrate tooling into an agent-ready

Everpure (NYSE: P) has evolved from storage pioneer to data platform, closing fiscal 2026 with $3.7 billion in revenue, its first billion-dollar quarter, and accelerating growth into FY27. Our strategic agenda spans the companies defining the next era of technology - hyperscalers, AI labs, the AI hardware supply chain, data platform providers, and the broader AI ecosystem. This type of work—work that changes the world—is what the tech industry was founded on. So, if you're ready to seize the endless opportunities and leave your mark, come join us. As an Application Engineer for AI Automation , you will be at the clinical edge of our intelligence layer. This isn't just about writing code; it's about architecting the nervous system of our automated enterprise. You will bridge the gap between heavy-duty enterprise platforms (Salesforce, Zuora, ServiceNow) and the next generation of Agentic AI. Your primary mission will be building high-performance Model Context Protocol (MCP) servers that allow AI agents to interact deeply with complex business logic—specifically within the Salesforce ecosystem (Quote, Opportunity, and Renewal services). You’ll move from building RAG-based retrieval to orchestrating Agent-to-Agent communication , creating a seamless autonomous workflow across our tech stack. Key Responsibilities Architect MCP Servers: Design and implement robust MCP servers to expose Salesforce services (Quote, Opportunity, Renewal) and other core platforms to AI agents. Data Model Synthesis: Rapidly decompose the data models of enterprise applications like Zuora, Salesforce, and ServiceNow to build effective schemas for AI interaction. Build AI Pipelines: Develop and optimize Retrieval-Augmented Generation (RAG) workflows and AI agents that can execute complex tasks with minimal human intervention. Agentic Orchestration: Lead the transition from simple chatbots to Agentic AI , focusing on multi-agent collaboration and autonomous "Agent-to-Agent" communication. Integra

About the Team DoorDash’s GenAI Platform team sits within Machine Learning Platform and builds the shared infrastructure that helps DoorDash, Wolt, and Deliveroo teams safely bring GenAI-powered products, agents, automation, and personalization to production. Our mission is to increase the velocity of business impact from GenAI. A central pillar of that work is our evaluation platform — the unified evals backbone that lets teams measure, trace, and trust the quality of LLM and agent systems across the company, powering trace/score ingestion, LLM-as-judge workflows, agent simulations, and LLM observability for the tens of millions of daily requests flowing through our LLM Gateway. We also own core platform surfaces including the Agent Gateway, open-weights model serving and batch inference, guardrails, and cost attribution. About the Role You will join a small, high-leverage team building production infrastructure for Generative AI at DoorDash, with a primary focus on our evals and LLM observability platform: the systems that let teams evaluate, trace, and continuously improve the quality of LLM and agent products. You’ll work across evaluation frameworks and SDKs, OpenTelemetry-based trace/score ingestion, LLM-as-judge and offline/online eval pipelines, agent simulations, data pipelines, backend services, and observability. This role is ideal for an engineer who enjoys building reliable measurement and quality primitives in a fast-moving technical area where product needs, model capabilities, vendor ecosystems, and evaluation methodologies are evolving quickly. You’re excited about this opportunity because you will… Build the infrastructure that helps DoorDash teams move GenAI ideas from prototype to production, increasing the velocity of business impact from AI across the company. Work on our unified evals platform — evaluation SDKs, OpenTelemetry trace/score ingestion, LLM-as-judge, offline and online eval pipelines, and agent simulations — alongside the LLM Gatew

We’re looking for an experienced engineering leader to lead and scale Asana’s flagship AI Teammates Pillar within our Core/AI Organization. Reporting directly to the Head of Engineering, AI & AWM, you will oversee an engineering area encompassing four key teams: AI Teammates Platform (AITP), AI Teammates Experience (AITX), AI Chat Experience, and Agent Orchestration. In this role, you will lead engineering managers and senior technical leaders to drive the end-to-end strategy, execution, and architecture that define how humans and AI collaborate in Asana, turning frontier LLM capabilities into trusted, reliable, high-value product workflows for enterprise customers worldwide. This role is based in our San Francisco office with an office-centric hybrid schedule. The standard in-office days are Monday, Tuesday, and Thursday. Most Asanas have the option to work from home on Wednesdays. Working from home on Fridays depends on the type of work you do and the teams with which you partner. If you're interviewing for this role, your recruiter will share more about the in-office requirements. What you’ll achieve Drive Strategy & Execution Across the AI Teammates Pillar: Lead, set direction, and align goals/metrics across four core engineering teams (Platform, Experience, Chat, and Agent Orchestration) to execute on Asana’s flagship AI vision while balancing business, customer, and technical needs. Architect Enterprise-Grade AI Platforms & Systems: Own the end-to-end technical strategy across model rollouts, eval infrastructure, tool orchestration, Model Context Protocol (MCP), and proactivity engines—enabling Asana to operate reliable agentic systems for top-tier enterprise customers. Define Next-Generation Human-AI Collaboration: Lead product and platform engineering teams delivering full-screen and docked chat surfaces, discovery/onboarding flows, in-product explainability, human-in-the-loop workflows, and ROI/governance experiences for admini

About Pinterest: Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product. Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the flexibility to do your best work. Creating a career you love? It’s Possible. At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI. Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here . About the Team: Hundreds of millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love. Within Pinterest, the Pinterest Labs organization focuses on applied ML research and development to power the platform. Labs works across a broad variety of AI/ML initiatives, including LLMs/VLM, agent design, core computer vision, multimodal representation learning, visual generative modeling, recommender systems, graph learning, and more. This is the group that develops the foundation AI models that fully leverage the hundreds of billions of Pins and the associated knowledge graphs, and ships new product capabilities to fully utilize these technologies. We are curre

ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F , led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to to ship AI products. THE ROLE: Voice is becoming the internet’s next interface, but a production-grade Voice AI system is "hard to build" . You’ll join a small founding team of Baseten Voice AI, focused on bringing state-of-the-art open source models into production for Voice AI customers across productivity, customer service, clinical conversation, creator tools, education, and more. You’ll make a meaningful impact on people’s daily lives and help reshape these industries. This is a high-impact, high-ownership role. You will be the primary owner of Baseten Voice AI - our in-house inference stack to power Voice AI models - from product roadmap through engineering implementation. You’ll partner closely with Forward Deployed Engineers, Model Performance Engineers, and sister engineering teams to push the boundaries of Voice AI. EXAMPLE INITIATIVES: Develop world-class model serving stack for state-of-the-art open-source voice models - reduce end-to-end and tail latency (p95/p99), increase throughput, and improve GPU efficiency via profiling, runtime tuning, and server-level optimizations. Build large-scale, real-time infrastructure for multi-model voice agents - orchestrate STT, TTS, and agent components with streaming I/O to meet customer SLOs. Design tight training and inference iteration loops for voice model customization - enable fast evaluation, safe rollout, and rapid experimentation for custom voice model development. Past projects:

For over 20 years, Smartsheet has empowered teams to manage work seamlessly and scale solutions smarter. Now, in our most ambitious chapter yet, we are uniting human teams with AI agents. By orchestrating the work agents do best, automating manual tasks and uncovering insights at scale, we create the space for people to focus on what truly matters: judgment, creativity, and big thinking. That is magic at work, and it’s what we show up for every day. You independently lead the most complex AI deployments Smartsheet undertakes. You own the full engagement lifecycle from technical discovery through production deployment through solutions org handoff. You architect multi-agent solutions, design client-personalized MCP resource packs, and build the Deployment Kits that transform how 200+ solutions consultants and partners operate. You mentor junior FDEs, drive the intelligence loop, and present field findings at weekly Applied AI strategy sessions. You are building a function, not filling a role. What You Will Do Lead complex, multi-system AI deployments end-to-end scope, architect, build, validate, and manage the customer relationship throughout. Own the AI workshop program for your pod, customize modules per customer, lead technical sessions, translate outputs into production requirements, evolve content from field learning. Architect multi-agent solutions selecting the right coordination pattern for each customer’s workflow characteristics and compliance requirements. Design client-specific and industry-specific MCP resource packs that serve personalized intelligence from the server so every connected AI surface gets smarter for that customer automatically. Own Deployment Kit quality for your pod. If a kit is not documented well enough for a solutions consultant with no engineering background to follow, it isn’t done. Lead Solutions Enablement Sprints: transfer AI deployment patterns to solutions consultants and partners with training materials and certification crite

For over 20 years, Smartsheet has empowered teams to manage work seamlessly and scale solutions smarter. Now, in our most ambitious chapter yet, we are uniting human teams with AI agents. By orchestrating the work agents do best, automating manual tasks and uncovering insights at scale, we create the space for people to focus on what truly matters: judgment, creativity, and big thinking. That is magic at work, and it’s what we show up for every day. You independently lead the most complex AI deployments Smartsheet undertakes. You own the full engagement lifecycle from technical discovery through production deployment through solutions org handoff. You architect multi-agent solutions, design client-personalized MCP resource packs, and build the Deployment Kits that transform how 200+ solutions consultants and partners operate. You mentor junior FDEs, drive the intelligence loop, and present field findings at weekly Applied AI strategy sessions. You are building a function, not filling a role. What You Will Do Lead complex, multi-system AI deployments end-to-end scope, architect, build, validate, and manage the customer relationship throughout. Own the AI workshop program for your pod, customize modules per customer, lead technical sessions, translate outputs into production requirements, evolve content from field learning. Architect multi-agent solutions selecting the right coordination pattern for each customer’s workflow characteristics and compliance requirements. Design client-specific and industry-specific MCP resource packs that serve personalized intelligence from the server so every connected AI surface gets smarter for that customer automatically. Own Deployment Kit quality for your pod. If a kit is not documented well enough for a solutions consultant with no engineering background to follow, it isn’t done. Lead Solutions Enablement Sprints: transfer AI deployment patterns to solutions consultants and partners with training materials and certification crite

For over 20 years, Smartsheet has empowered teams to manage work seamlessly and scale solutions smarter. Now, in our most ambitious chapter yet, we are uniting human teams with AI agents. By orchestrating the work agents do best, automating manual tasks and uncovering insights at scale, we create the space for people to focus on what truly matters: judgment, creativity, and big thinking. That is magic at work, and it’s what we show up for every day. You independently lead the most complex AI deployments Smartsheet undertakes. You own the full engagement lifecycle from technical discovery through production deployment through solutions org handoff. You architect multi-agent solutions, design client-personalized MCP resource packs, and build the Deployment Kits that transform how 200+ solutions consultants and partners operate. You mentor junior FDEs, drive the intelligence loop, and present field findings at weekly Applied AI strategy sessions. You are building a function, not filling a role. You will work remotely from Germany and will be reporting to Sr. Director, Engineering You Will: Lead complex, multi-system AI deployments end-to-end scope, architect, build, validate, and manage the customer relationship throughout. Own the AI workshop program for your pod, customize modules per customer, lead technical sessions, translate outputs into production requirements, evolve content from field learning. Architect multi-agent solutions selecting the right coordination pattern for each customer's workflow characteristics and compliance requirements. Design client-specific and industry-specific MCP resource packs that serve personalized intelligence from the server so every connected AI surface gets smarter for that customer automatically. Own Deployment Kit quality for your pod. If a kit is not documented well enough for a solutions consultant with no engineering background to follow, it isn't done. Lead Solutions Enablement Sprints: transfer AI deployment patterns to so

We’re looking for an experienced engineering leader to lead and scale Asana’s flagship AI Teammates Pillar within our Core/AI Organization. Reporting directly to the Head of Engineering, AI & AWM, you will oversee an engineering area encompassing four key teams: AI Teammates Platform (AITP), AI Teammates Experience (AITX), AI Chat Experience, and Agent Orchestration. In this role, you will lead engineering managers and senior technical leaders to drive the end-to-end strategy, execution, and architecture that define how humans and AI collaborate in Asana, turning frontier LLM capabilities into trusted, reliable, high-value product workflows for enterprise customers worldwide. This role is based in our San Francisco office with an office-centric hybrid schedule. The standard in-office days are Monday, Tuesday, and Thursday. Most Asanas have the option to work from home on Wednesdays. Working from home on Fridays depends on the type of work you do and the teams with which you partner. If you're interviewing for this role, your recruiter will share more about the in-office requirements. What you’ll achieve Drive Strategy & Execution Across the AI Teammates Pillar: Lead, set direction, and align goals/metrics across four core engineering teams (Platform, Experience, Chat, and Agent Orchestration) to execute on Asana’s flagship AI vision while balancing business, customer, and technical needs. Architect Enterprise-Grade AI Platforms & Systems: Own the end-to-end technical strategy across model rollouts, eval infrastructure, tool orchestration, Model Context Protocol (MCP), and proactivity engines—enabling Asana to operate reliable agentic systems for top-tier enterprise customers. Define Next-Generation Human-AI Collaboration: Lead product and platform engineering teams delivering full-screen and docked chat surfaces, discovery/onboarding flows, in-product explainability, human-in-the-loop workflows, and ROI/governance experiences for admini