About the role We’re looking for an engineering manager to lead a team building software systems that detect and prevent harmful misuse of frontier AI models—before incidents occur. This is a builder’s role: you’ll lead engineers shipping production services, detection pipelines, and mitigation mechanisms that protect frontier model integrity and reduce high-severity misuse risk. While this work intersects with frontier model development, security and risk, we’re explicitly seeking someone with a software engineering foundation who is comfortable building reliable systems that can operate at billions of users scale. In this role you will: Lead a team of software engineers building detection + mitigation systems for frontier model misuse, with an emphasis on model IP protection / distillation detection and emerging risk surfaces from autonomous agents. Set the technical roadmap and execution strategy: prioritize, design, ship, iterate, measure impact. Build production systems: services, pipelines, tooling, instrumentation, and automation that scale with frontier model usage. Partner deeply with Research and Product to translate evolving model capabilities into concrete tests, signals, and mitigations that can be deployed at scale. Drive strong engineering fundamentals: architecture, reliability, monitoring, performance, and operational excellence. Hire and grow an exceptional team across backend, data systems, and applied ML engineering domains as needed. Anticipate what breaks at scale as agentic workflows become more capable. You might thrive in this role if you: Experience building systems in adversarial, fast-evolving environments Are comfortable with ambiguity and novelty Have experience adjacent to security (e.g., abuse prevention, fraud, integrity, platform defense, auth/identity, malware/spam, adversarial environments) Communicate clearly and build trust quickly with senior stakeholders—pragmatic, collaborative, and calm under scrutiny. Significant experience
Jobs in United States
Lead Automation Engineer in United States
2,434 active opportunities · Updated October 2026
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15 jobs
Explore current lead automation engineer jobs across United States. Filter by work mode, employment type, experience, department, date posted and distance.
At Vanta, our mission is to help businesses earn and prove trust. We believe that security should be monitored and verified continuously, and we empower companies to practice better security and prove it with ease. Vanta has a kind and talented team, and while some have prior security experience, many have been successful at Vanta without it. As a Staff Software Engineer on the Automation - Foundations team, you will lead the re-platforming of the data layer underneath Vanta’s entire compliance product. This is a migration that spans multiple teams, has to preserve every public API contract along the way, and cannot lose a single customer’s evidence while it happens. Foundations is Vanta’s data platform team. We ingest security and compliance data from across our customer’s environments, currently tens of thousands of resources per second, with single-customer bursts running into the millions. We store the data, catalog it, make it queryable, and turn it into evidence that has to survive a real SOC 2 or FedRAMP audit. We are in the middle of moving our platform from a Mongo-centric architecture to a schema-aware, Postgres-backed architecture, on a Kafka and S3 pipeline that decouples data fetching from processing. Both pipelines run in parallel today, the hard problems here are correctness under migration, eventual consistency, and multi-tenancy, in a domain where “mostly right” is not an acceptable failure mode. Visit our Vanta Engineering Blog to learn more about what our team is working on. What you'll do as a Staff Software Engineer at Vanta: Lead the migration of Vanta’s resource data model from a Mongo-centric solution to a schema-aware Postgres-backed solution and running both generations in parallel without breaking a customer integration. Drive solutions across teams that you do not own but are dependent on the platform built by your team. Design for correctness under eventual consistency with idempotent session handling, conditional writes that survive out
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
NVIDIA’s EDA Infrastructure organization builds and operates the systems that support chip development. We are looking for an engineering manager to lead the team responsible for operational processes and platforms across incident management, maintenance, on-call, issue management, and customer-serving readiness. You will own the roadmap and delivery, from defining how teams work to building the tools they use. You will partner with infrastructure and service owners to improve reliability, reduce manual work, and ensure services are ready to support customers. Your team will use automation, AI, and lessons from operational events to drive improvements. What you’ll be doing: Lead a team and own the roadmap for operational processes and platforms, from requirements and delivery through adoption and results. Set technical direction, prioritize work, and guide execution across engineering and operational disciplines. Partner with infrastructure, product, and security teams to establish consistent practices for incident response, maintenance, on-call, issue management, and customer-serving readiness. Hire and develop engineers and technical leads, building a team with clear ownership and accountability. Align priorities across teams, communicate progress and risks, and provide technical leadership during major incidents. What we need to see: <span style="co
$200K – $260K/yr
The Forward Deployed Engineer, Staff (FDE) is a high impact technical leader responsible for translating the immense power of Talkdesk's Agentic AI platform into transformative, production grade solutions for our strategic enterprise customers. You are a unique blend of a highly experienced software engineer, a technical project lead, and a hands-on builder. You own the technical execution for deployments, mitigate technical risks, and drive successful customer outcomes across assigned projects. This role is for the experienced builder who excels in high stakes, customer facing environments and is passionate about defining the future of Customer Experience Automation. Responsibilities Technical Project Leadership & Architecture: Act as the technical lead for complex deployments. Design and implement the architectural blueprint for AI agent solutions, manage cross-system dependencies, and ensure designs meet stringent enterprise standards for security and scale. Hands-On Engineering & Delivery: Write production-grade code and leverage Talkdesk and 3rd-party APIs/SDKs to design, build, test, and deploy AI agents. Drive the execution from prototype through to production deployment, ensuring technical quality. Technical Consultation & Alignment: Serve as a trusted technical expert for our AI solutions. Confidently address deep technical inquiries, mitigate technical risk, and build trust with customer Engineering Directors, and technical architects. Influence Product & Engineering Roadmap: Synthesize and codify deployment learnings into reusable solution patterns and tooling. Provide actionable feedback to core Product and Engineering teams to help inform future product direction. Technical Guidance: Mentor junior FDEs and technical specialists on best practices for complex AI architecture, production quality, and client-facing technical delivery. Who You Are We are looking for an autonomous, results-driven technical leader who thrives at the intersectio
From $131K/yr
Role Overview You’re a seasoned Site Reliability Engineer who loves owning complex infrastructure, making things run faster, safer, and with less manual effort. In this Staff‑level role, you’ll design and operate VMware‑based private cloud platforms that power mission‑critical SaaS products used by customers around the world. You’ll work across Linux, Windows Server, networking, storage, and automation frameworks to increase reliability, reduce toil, and modernize a global datacenter environment. You’ll have the scope to set technical direction, build automation at scale, and mentor engineers while staying hands‑on with VMware vSphere, F5/AVI load balancers, and hybrid Active Directory. Here’s a breakdown of what you’ll do (not all of it, just the important stuff) Lead the architecture, deployment, and ongoing optimization of VMware vSphere–based private cloud infrastructure across multiple global datacenters. Design and build automation using PowerShell/PowerCLI, Ansible, Python, and CI/CD tools to streamline provisioning, configuration, and compliance. Administer, harden, and troubleshoot Linux (RHEL/CentOS/Ubuntu) and Windows Server environments that host enterprise and SaaS workloads. Integrate and manage Active Directory for authentication, access control, and service accounts across hybrid on‑prem and cloud environments. Partner with network and security teams to manage firewalls, VPNs, storage, and load balancers (F5 BIG‑IP, AVI/NSX Advanced Load Balancer) for highly available services. Document architectures and runbooks, participate in on‑call and change management, and mentor engineers while influencing long‑term reliability and automation strategy. These are the essentials you’ll need to get an interview 10+ years of experience in systems or infrastructure engineering, including operating large‑scale enterprise or SaaS datacenter environments. Deep hands‑on expertise with VMware vSphere (ESXi, vCenter, DRS, HA, vMotion, distributed switches) in production
From $131K/yr
Help shape the technology that enables a global organisation to do its best work. As Senior Manager, Platform Engineering, you’ll lead the team responsible for Diligent’s Atlassian and Microsoft platforms while setting the architectural direction for the wider internal IT estate. You’ll combine people leadership, enterprise platform strategy and hands-on technical judgement to create secure, reliable and scalable experiences for employees worldwide. From modernising service management and automating joiner, mover and leaver processes to enabling AI safely through Microsoft Copilot and Atlassian Rovo, your work will reduce friction, strengthen governance and deliver measurable business impact. Working across IT, Security, HR, Finance, Legal, Compliance and business teams, you’ll turn complex requirements into well-governed platforms that are easy to use, resilient and ready for the future. Here’s a breakdown of what you’ll do (not all of it, just the important stuff) Lead, coach and grow a global team of platform engineers and systems administrators, building a high-performing and inclusive culture. Own the strategy, architecture, governance and roadmap for Atlassian Cloud, including Jira, Jira Service Management, Confluence, Atlassian Guard and Rovo. Set the direction for Diligent’s Microsoft 365 E5 estate, including Teams, SharePoint, Exchange Online, Intune, Defender, Purview, Power Platform and Copilot. Design scalable integration and automation patterns across identity, HRIS, ITSM and business systems using APIs, event-driven automation, Okta Workflows, Power Platform and scripting. Partner with IT Support to improve self-service, automate repetitive work and reduce ticket volume, escalation effort and time to resolution. Establish strong standards for security, access governance, AI adoption, reliability, compliance and business continuity across the internal technology estate. These are the essentials you’ll need to get an interview Significant experience in i
About the Team The Finance Platform & Technology team builds and scales the systems and data architecture that power OpenAI’s core financial operations. We enable business agility, compliance, and operational excellence across procure-to-pay, quote-to-cash, supply chain, financial planning, and asset management. We partner with Procurement, Accounting, Tax, Legal, Security, Data, and Engineering to modernize workflows through thoughtful platform design, reliable integrations, scalable automation, and trusted data. About the Role As a Business Systems Lead for Procure-to-Pay, you will be a hands-on engineer who designs, builds, and operates the integrations and first-party applications that power OpenAI’s procurement workflows. You will translate business needs into secure, scalable software, APIs, data flows, and automation across Oracle Fusion, Zip, and connected platforms. You will build the future of buying at OpenAI using OpenAI’s own technology, from guided intake and approval experiences to supplier onboarding, purchasing, receiving, invoicing, and downstream financial data flows. You will own the technical roadmap and support model for these capabilities, improving today’s platforms while deciding where to integrate, configure, or build as OpenAI scales. Your core strength will be software and integration engineering. You will personally write code, troubleshoot cross-system failures, and take solutions through testing, deployment, and production support. You will also make targeted functional configurations in procurement platforms and partner with functional specialists on deeper process and module design. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: Design, build, and operate integrations across Oracle Fusion, Zip, and connected systems using APIs, events, messaging, and batch interfaces where appropriate. Build first-party
About the Team The Growth Platforms team builds the systems and operating foundations that help OpenAI grow responsibly. We partner across the product portfolio to connect customer signals, identity and consent, campaign workflows, measurement, and product experiences into an AI-enabled growth engine. Our work helps teams launch, learn, and scale with a high bar for data quality, privacy, reliability, and customer trust. About the Role We’re looking for an experienced marketing technology and operations leader to drive cross-functional work at the intersection of growth, measurement, data, and automation. Your mission will be to turn fragmented tools, signals, and workflows into reliable, measurable, AI-enabled capabilities that teams can use safely at scale. You’ll work across Growth, Marketing Operations, Product, Engineering, Data Engineering, Data Science, Security, Privacy, Legal, and Revenue Operations, as well as external advertising platforms, measurement providers, and implementation partners. You’ll translate business requirements and privacy constraints into data contracts, integration designs, rollout plans, and reliable first-party data systems. This is a hands-on, high-impact role for someone who brings structure to ambiguity and moves from event schemas, APIs, and data quality assurance to operating cadences, partner enablement, and executive updates. This role is based in San Francisco or New York City with a hybrid office expectation. In this role, you will: Own the operating model for Growth’s marketing technology stack across identity, consent, audiences, activation, measurement, and experimentation. Own and operate the complete paid-media tracking and measurement system, including website pixels, server-to-server conversion events, mobile measurement integrations, identity and consent controls, attribution methods, and timely signal delivery to advertising platforms. Design and implement event schemas, data mappings, APIs, and integrations; valid
At Freddie Mac, our mission of Making Home Possible is what motivates us, and it’s at the core of everything we do. Since our charter in 1970, we have made home possible for more than 90 million families across the country. Join an organization where your work contributes to a greater purpose. Position Overview: We are seeking an experienced and motivated Senior Software Engineering Manager to drive the strategic execution and delivery of enterprise platform technology, ensure alignment with business objectives , seamless integration, compliance with regulations, and operational excellence. Our Impact : Enterprise Business Technology Office (EBTO) support s multiple verticals by crafting and creating solutions to a variety of technology challenges. This support takes many forms, including delivering automation solutions by building and enhancing software applications using Business Process Management and Low Code Application Platforms required for Internal Audit, Legal and various other divisions at Freddie Mac. Enterprise Business Technology portfolio delivers foundational technology capabilities that power secure, scalable, and innovative technology for the organization using best-in-class tooling and standards across multiple functional domains. Your Impact: As a Senior Software Engineering Manager , you will lead the evolution of our C
Our Purpose Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we’re helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential. Title and Summary Senior Software Engineer Overview Join a team focused on transforming how Mastercard's payment systems are built, scaled, and operated. As a Senior Software Engineer, you will lead the design and development of cloud-ready applications, microservices, and distributed systems that support large-scale payment processing platforms while helping advance modernization, automation, and engineering excellence across the organization. In this role, you will contribute to software architecture decisions, drive technical design discussions, and partner with engineers to deliver scalable, resilient, and maintainable software solutions. You'll have the opportunity to solve complex technical challenges, mentor other engineers, and influence how software is designed, developed, tested, and supported across critical technology platforms. What You Will Do •Design software solutions and contribute to software architecture decisions that support scalability, maintainability, and operational excellence. •Translate complex product requirements into technical designs and implementation plans. •Lead development of modular, extensible, high-performance applications. •Design and implement comprehensive unit, functional, and integration testing strategies. •Analyze, optimize, and improve application performance, scal
About the Team OpenAI’s Hardware organization develops AI-native silicon and system-level solutions for the unique demands of advanced AI workloads. Building on efforts like Jalapeño, the team is developing future generations of AI-native silicon and tightly integrated systems to power the next generation of frontier models. By co-designing chips, systems, tools, and methodologies, the team helps deliver faster, more efficient, and production-ready hardware for OpenAI’s supercomputing platform. About the Role You will work on the systems software strategy and execution that brings new AI silicon from first power-on to a fully integrated system running production-representative models at expected functionality and performance. You will define how software exercises and validates compute, memory, interconnect, and I/O subsystems, then build the diagnostics, automation, and observability needed to find issues quickly. This role sits at the center of silicon, firmware, platform, systems, and workload teams. You will turn hardware specifications and performance targets into an end-to-end bringup plan, drive cross-functional debug, and establish the stress and regression infrastructure that makes each new platform reliable across operating environments. In this role, you will: Contribute to the end-to-end software bringup and validation strategy for new silicon and first-party systems. Define software-driven test coverage across compute, memory, interconnect, I/O, and their system-level interactions. Build diagnostics, test automation, telemetry, and regression infrastructure that accelerate first-silicon learning and issue isolation. Lead bringup from initial silicon arrival through board and system integration, docking, runtime enablement, and model execution. Design stress tests that characterize reliability, performance, and stability across workloads and operating conditions. Translate architecture specifications and performance models into measurable acceptance crit
From $137K/yr
The Code Gen team is tasked with building AI-powered code transformation tools that transform rigid, legacy applications that suffer from poor scalability and high operating costs into modern, microservices-based architectures that are built on top of MongoDB. Join our team and be at the forefront of innovation and creativity. We are looking for a Staff Engineer with domain expertise and years of experience in modernizing legacy applications that are based on traditional database systems. A significant advantage is profound prior experience in leveraging AI, particularly LLMs and GenAI capabilities, to enable reliable, self-driving automation of the code transformation, iterative build, and test processes. In this role, you will be instrumental in initiating technical strategies and ideas, lead the Code Gen team in designing, building, and optimizing our code transformation workflow and tools. You will work on critical components that ensure the scalability, efficiency, and reliability of our services. This involves crafting sophisticated orchestration layers, robust integration points, and high-performance data systems that seamlessly connect and leverage advanced AI capabilities for code generation, build and test. This role will be based remotely in North America. A strong candidate for this position will have Extensive experience (8+ years) in software development and operations, with a proven track record of delivering high performance, correctness, and architectural excellence in fast-paced environments Experience using Relational Databases such as Oracle, MySQL, Microsoft SQL Server or PostgreSQL Experience with tools and methodologies for code analysis, refactoring, and automated testing Experience in designing and implementing complex software systems, collaborating effectively with engineers of all experience levels to achieve high reliability and performance Practical knowledge of integrating GenAI into large-scale, complex systems, including a clear unde
About the Team The Ads Support Delivery team is responsible for helping successfully operate and grow on our Ads product. This includes technical guidance, troubleshooting complex delivery and monetization issues, and partnering closely with Product, Engineering, Trust & Safety and Go-To-Market teams to resolve customer-impacting problems and improve the platform over time. The team’s mission is to deliver a high-quality customer experience at scale by combining strong human support with automation, self-service, and AI-enabled workflows, while maintaining high operational rigor. About the Role: As a Support Delivery Lead for Ads, you will lead a team responsible for end-to-end support delivery across the ads ecosystem, including campaign setup, delivery, billing, measurement, and policy navigation. You will set the operational bar for quality, responsiveness, and consistency; coach and grow the team; and translate support signals into actionable improvements with Engineering, Product, and Go-To-Market partners. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: Lead and support a team of Ads support engineers, ensuring they have the tools, clarity, and coaching needed to operate at a high bar in a technically complex domain. Set clear expectations and operating standards, run recurring performance reviews, and build development plans that grow both technical depth (ad tech fluency) and customer-facing excellence. Design and continuously improve support coverage for ad buyers, ensuring the team can diagnose delivery issues and monetization and integration issues with equal rigor. Act as the bridge between Support Delivery, Engineering, Product, and Go-To-Market teams. Drive alignment on priorities, escalation paths, launch readiness, tooling improvements and mechanisms to reduce repeated customer pain points. Partner with engineering teams
About the Team OpenAI is building the infrastructure foundation for the next generation of AI. The Data Center Engineering team defines the strategy, reference architectures, technical requirements, and delivery standards for the large-scale data centers that support OpenAI research, products, and infrastructure partners. As a Data Center Controls Network Engineer, you will design, validate, and scale the controls and OT network architectures that support high-density AI data centers. You will work across controls systems, OT infrastructure, telemetry, commissioning, deployment, and operations, partnering with mechanical, electrical, IT/networking, security, and external delivery teams. About the Role We are seeking a mid to senior OT Network Engineer with a strong controls systems background to lead the design and operation of resilient, secure, and scalable OT network architectures for high-density AI data centers. This role translates compute, power, cooling, and operational requirements into practical OT network designs, evaluates vendor solutions, and drives technical decisions across controls infrastructure, telemetry, commissioning, and operations. The ideal candidate has strong hands-on experience in mission-critical OT environments, including industrial networking, virtualized infrastructure, and OT network operations, with expertise in routing, switching, segmentation, firewall policy, time synchronization, monitoring, and network lifecycle support. Key Responsibilities Define controls, automation, and OT network requirements for AI data center campuses. Develop reference architectures, engineering standards, and reusable design templates. Review and develop basis-of-design and functional design documents, including OT network diagrams, IP/VLAN schemes, telemetry architectures, data flow diagrams, and commissioning requirements. Design OT and infrastructure network architectures, including physical topology, logical topology, IP addressing, subnetting, VLA
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