Ai Operations Director Jobs

About the Team pAGI Infra team builds and operates the systems that make large-scale model training and evaluation reliable, efficient, and easy to run. Our work spans distributed training infrastructure, inference and grading platforms, compute scheduling, and research tooling. We partner closely with researchers and engineering teams to turn new research needs into dependable infrastructure, improve GPU efficiency, and shorten the path from an experiment to a validated model. About the Role We’re looking for an AI Systems Engineer to help scale the infrastructure behind our training and evaluation workflows. You’ll own projects from identifying bottlenecks and designing solutions through deployment and operation. The work combines distributed systems engineering, performance optimization, and close collaboration with researchers. You might build a shared grading service, improve resource allocation across workloads, or bring a new training stack into production — directly improving how quickly and reliably research moves forward. In this role, you will: Build and operate infrastructure for large-scale training and evaluation, improving reliability, throughput, and resource efficiency. Develop shared inference and grading platforms with automated capacity management, health monitoring, and visibility into performance. Improve compute scheduling and resource allocation to reduce idle GPU time and help workloads recover quickly from failures. Diagnose bottlenecks across training, inference, and orchestration, and work across teams to improve end-to-end performance. Build self-service tools, automated validation, and observability that help researchers launch experiments, diagnose issues, and compare results with less manual intervention. You might thrive in this role if you: Are excited about the potential of personal AGI and want to build the infrastructure that enables it. Have strong software engineering fundamentals and experience building or operating large-scal

Our vision is to transform how the world uses information to enrich life for all . Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever. Responsibilities include, but not limited to: Demonstrate Micron core values People, Innovation, Tenacity, Teamwork, and Customer Focus Collecting requirements from customer requests to ensure flawless application development Crafting, developing, debugging, documenting, testing, and deploying applications with world-class precision Collaborating ambitiously with other developers on the team to foster a strictly inclusive environment Working closely with Business Operation Teams, Product and Application Development teams, and other internal customers during application development and deployment to successfully implement solutions Training users on the use and maintenance of new applications to ensure seamless integration Implementing 3rd party solutions and partnering with the IT Procurement representative to resolve contracts, support requirements, training provided, etc. Applying AI-enabled ways of working to improve application development processes Join Micron and be part of an exceptionally innovative team dedicated to making a global impact! About Micron Technology, Inc. We are an industry leader in innovative memory and storage solutions transforming how the world uses information to enrich life for all . With a relentless focus on our customers, technology leadership, and manufacturing and operational excellence, Micron del

Bits Code is Datadog’s cloud coding agent which fixes the problems that Datadog surfaces, as automatically as possible. You’ll shape the architecture, tools, processes, and culture that keep security risk very low while working hands-on with the team to ship product features quickly. At Datadog, we place value in our office culture - the relationships that it builds, the creativity it brings to the table, and the collaboration of being together. We operate as a hybrid workplace to ensure our employees can create a work-life harmony that best fits them. What You'll Do: Own the security architecture and implementation of Bits Code from early design through production operation. Work with engineering, product, infrastructure, and security teams to identify risks and shape the product. Build threat models for new and existing agent risks such as prompt injection. Help the team ship secure software fast by writing and maintaining core libraries, and guiding processes and culture. Work with our sandbox teams on how Bits Code executes untrusted workloads. Be on call. Datadog culture is that you build it, you run it. Who You Are: You have a BS/MS/PhD in Computer Science, Engineering, or a related scientific field, or at least 5+ years of professional experience, with a background in product security, application security, or security architecture. You have experience securing systems that operate across complex trust boundaries. You have experience building and operating full stack systems at scale. You are familiar with security risks in agentic systems and have experience designing against them. You make pragmatic security trade-offs. Datadog values people from all walks of life. We understand not everyone will meet all the above qualifications on day one. That's okay. If you're passionate about technology and want to grow your skills, we encourage you to apply. Benefits and Growth: Skilled, knowledgeable, and kind teammates to work with a

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

Fanatics Commerce is the global leader in licensed sports merchandise, operating a vertically integrated platform that designs, manufactures, and delivers officially licensed apparel, jerseys, headwear, and collectibles for major leagues, teams, and events worldwide. With more than 900 e-commerce sites and a global omnichannel presence across digital, in-venue, and retail, Fanatics Commerce reaches fans in over 180 countries and powers official fan experiences for many of the world's most iconic sports properties. At Fanatics, we bring our BOLD Leadership Principles to life every day - building championship teams, obsessing over fans, acting with entrepreneurial speed, and delivering with a determined and relentless mindset. As we continue to scale our global platform, the Staff Product Manager, AI Platform Control Plane will play a critical role in defining the strategy, governance, and scalable foundation for AI agents, tools, and applications across Fanatics Commerce. ROLE OVERVIEW Fanatics Commerce is building an AI platform to make it easier for teams to build, deploy, and scale AI-powered agents and tools across the organization, and the Staff Product Manager, AI Platform Control Plane owns the common capabilities that make this possible — registration, configuration, deployment, lifecycle management, security, governance, monitoring, and operation at scale. This role sits at the intersection of product, engineering, AI, security, and business needs, working as part of a globally distributed AI platform PM team alongside the AI Platform Adoption PM and the Business Solutions PM to create a continuous feedback loop between customer needs, business solutions, and platform evolution. The Staff Product Manager, AI Platform Control Plane delivers business and fan impact through BOLD leadership and execution excellence, leveraging data, automation, and AI-enabled insights. HOW WILL YOU DRIVE IMPACT Success is measured by the ability to deliver results through BOLD c

Location: Doha, Qatar | Practice Area : Technology & Engineering | Type: Permanent The Role Capco is looking for an AI Security Consultant to help our clients identify, assess, and manage security risks associated with AI technologies and AI-enabled solutions. You’ll work across data, security, technology, risk, and business teams to embed appropriate security controls throughout the lifecycle of AI systems. This is an opportunity to work at the intersection of AI, data, and cybersecurity within financial services, helping clients adopt AI securely while protecting sensitive information, strengthening governance, and managing emerging security risks. What You’ll Do Assess security risks associated with AI systems, models, data pipelines, and supporting technology environments. Conduct AI security assessments and secure AI architecture reviews. Define and implement security controls, standards, and guardrails across the AI lifecycle, from design and development through deployment and ongoing operation. Identify and assess AI-specific threats and vulnerabilities, including risks relating to data exposure, model access, prompt manipulation, and misuse. Deliver cybersecurity advisory services supporting enterprise AI adoption. Support clients in securing AI-enabled products, platforms and data ecosystems. Work with data, security, architecture, engineering, risk, and business teams to embed security-by-design into AI solutions and delivery processes. Support AI security governance, risk assessments, control testing, monitoring, incident response, and remediation activities. What We’re Looking For Strong experience in cybersecurity, information security, AI security, data security, or related technology risk disciplines. Practical understanding of AI and machine learning environments and the security risks associated with models, data, applications, and supporting infrastructure. Experience applying security controls, threat modelling, risk assessment, identity and a

About Snorkel Snorkel AI is the frontier AI data lab, helping teams build the data and environments behind high-performing frontier and agentic AI. We combine technology with research-driven AI data development to create datasets, benchmarks, evals, and custom solutions for real-world AI systems. Founded out of the Stanford AI Lab in 2019, Snorkel works with leading AI labs and enterprises to move from better data to better outcomes. Excited to help us redefine how AI is built? Apply to be the newest Snorkeler! We’re looking for a Research Scientist to advance how high-quality data and environments for AI agents are created. You’ll build and optimize pipelines that combine real-world data, automated generation, and human expert input. Working with domain experts, academic partners, customers, and our product and engineering teams, you’ll scale these pipelines to target frontier model performance gaps and expand data and environment diversity. Your work will amplify human knowledge and judgement, enabling experts to create and refine data and agentic environments that strengthens Snorkel’s position as the frontier data lab. This role is ideal for someone who wants to advance frontier AI through data and environment creation and enjoys turning research into reusable, scalable systems. Location: San Francisco, New York City, OR REMOTE Main Responsibilities Design, implement, and optimize reusable pipelines that combine AI capabilities with expert judgment to accelerate data and agentic environment creation. Design and run rigorous experiments to validate proof-of-concept approaches, measure their impact on data quality, pipeline efficiency, and model performance, and communicate findings. Partner with engineering, data operation, domain experts, and customers to turn research prototypes into reliable production workflows. Work directly with domain experts to design and test workflows that help them author, review, and refine data and environments. Work cros

Who We Are Simpplr is the AI-powered intranet for unifying the digital workplace. It brings people, trusted knowledge, apps, and agents into a coherent digital experience. Powered by a proprietary EX Knowledge Graph, Simpplr synthesizes signals and context across connected systems to deliver personalized information and actions. The platform serves as a digital hub supporting communications, engagement, employee services, and work. With low-code extensibility and enterprise-grade security and governance, Simpplr enables confident operation at scale. More than 1,000 organizations — including AAA, the NHS, Penske, and Moderna — trust Simpplr to keep their workforce informed, aligned, and productive. Learn more at simpplr.com . About the role We are looking for a Lead Voice AI Engineer to build production-grade Voice Agents for frontline heavy verticals like healthcare, manufacturing, warehousing, retail, hospitality focusing on employee support, procurement, collections, logistics, ordering etc. You will lead the design of low-latency, real-time voice systems combining ASR, TTS, LLMs, conversational AI, enterprise workflows, knowledge retrieval, compliance, and human handoff. This is a hands-on technical leadership role for someone who can take Voice AI from architecture to production. Responsibilities Design and build the real-time voice runtime for live conversations. Build and optimize streaming ASR, TTS, VAD, endpointing, turn-taking, and barge-in. Build adaptive voice pipelines for high-noise frontline environments (60-112 dB), hospitals, factory floors, warehouses, including server-side noise cancellation, echo suppression, and dynamic ASR/TTS optimization for PSTN and mobile phone audio quality. Architect multi-provider speech routing across a broad multilingual matrix, including code-switching (e.g., Spanglish, Hinglish), where no single ASR or TTS provider covers all languages, and language detection, provider selection, and fallback chains must operate

Why RoboForce RoboForce is an AI robotics company developing Physical AI–powered Robo-Labor for dull, dirty, and dangerous work. The company's robots are engineered for demanding industrial environments, with a focus on real-world deployment and scalability. We are looking for a Lead AI Research Engineer, Embodied Systems to lead and own the engineering of the systems that turn embodied AI into real-world robot behavior. You will be the technical owner and lead for the full embodied systems stack — the onboard AI system, the data collection system, the teleoperation systems, and the on-robot reinforcement learning system — driving the direction hands-on and closing the loop between data, models, and action in the physical world. Responsibilities Lead and own, from the engineering side, the embodied systems that power RoboForce's data flywheel — the onboard AI (inference) system, the data collection system, the teleoperation systems and the on-robot reinforcement learning system. Set the technical direction and architecture for how learned models run, are evaluated, and improve on real robots. Deliver these systems end-to-end on physical robots — from bring-up through reliable, real-time operation in demanding industrial environments. Own on-robot deployment and closed-loop evaluation of policies, turning real-world performance into measurable improvements. Partner with and influence the robotics software team and the ML research team to align interfaces and priorities across the stack. Grow the direction — mentor engineers and raise the technical bar for embodied systems work. Requirements Bachelor's or Master's degree in Computer Science, Robotics, Electrical Engineering, or related field with significant relevant experience, or a PhD degree. Track record of leading complex robotic or embodied systems end-to-end and setting technical direction for other engineers. Strong proficiency in both C++ and Python, with solid systems programming and real

We are looking for a Sr. Engineer to design, build, and scale the infrastructure powering NVIDIA’s AI agent ecosystem. You will work at the intersection of distributed systems, developer platforms, and agentic AI — building the foundational services that enable teams across the company to develop, deploy, orchestrate, and operate autonomous AI agents at production scale. What you will be doing: Build and develop platform services that manage the full agent lifecycle from registration through deployment, execution, and teardown Architect multi-tenant Kubernetes execution environments with pod lifecycle management, per-tenant namespace isolation, persistent storage, admission policy enforcement, and identity propagation Develop and maintain automated CI/CD pipelines using GitLab CI and ArgoCD, including reusable pipeline templates and deployment blueprints that standardize how agents are built across teams Build framework-agnostic infrastructure supporting multiple agent SDKs and harnesses — lifecycle hooks, skills configuration, memory services, and OTEL instrumentation — so teams can onboard new agent frameworks without platform changes Build and operate Kafka-based message pipelines and real-time event streaming using Redis PubSub and SSE Develop data ingestion pipelines, access interfaces, and storage layers that power AI agent knowledge and context Implement session management for state persistence, conversation history, and agent recovery across sessions Develop multi-layer auth using OAuth 2.0, JWT validation, token exchange, and gateway integration, and manage secrets lifecycle with Vault (provisioning, rotation, container injection) Partner with security teams on compliance, access controls, and approval workflows for agent operations What we need to see: Bachelor's or Master's degree in Computer Science, Engineering, or

The Platform team creates the technology that enables Spotify to learn quickly and scale easily, enabling rapid growth in our users and our business around the globe. Spanning many disciplines, we work to make the business work; creating the infrastructure, tooling, frameworks, and capabilities needed to welcome a billion customers. Enterprise AI builds and operates the internal AI platform layer that supports Spotifiers across the company. We’re helping evolve AI tooling into reliable infrastructure that teams can use in their day-to-day work. Our team builds the connective tissue between AI models and Spotify’s internal systems, with a focus on secure access, governance, identity, integrations, and dependable AI infrastructure. What You'll Do Design, build, and operate secure enterprise AI platform capabilities that connect AI models, agents, tools, and Spotify’s internal systems. Own major workstreams across our enterprise AI infrastructure, including our Model Context Protocol (MCP) gateway and enterprise context capabilities, from technical design through launch and operation. Build reliable backend services, APIs, and integrations that enable AI-powered experiences across Spotify’s digital workplace. Help develop scalable approaches to AI governance, including identity-aware access, permissions, auditing, policy enforcement, and managing risks associated with third-party AI-enabled tools. Design, build, test, and evaluate agentic systems and workflows that help Spotifiers access information and accomplish tasks effectively. Take operational ownership of the services and components you build, balancing speed, reliability, security, and long-term maintainability. Partner with engineers and stakeholders across Spotify to identify opportunities, make thoughtful technical tradeoffs, and turn emerging AI needs into scalable platform capabilities. Contribute to engineering practices, knowledge

P-1385 Companies are investing billions of dollars into developing and deploying AI and the data platforms that enable it. But do they know what is happening? At Databricks, we are passionate about enabling data teams to solve the world’s toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world’s best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers — and customer obsessed — we leap at every opportunity to tackle technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. And we're only getting started. As a Senior Software Engineer on the Customer Foresight Team , you'll lead the development of products that customers use to get insights on their AI and data workloads, optimize their performance, and lower costs. You will build data infrastructure that processes billions of entries daily, deploy to over 65 cloud regions worldwide, and enable some of the world's biggest companies to conduct their DevOps, FinOps, SecOps and AIOps jobs. This role requires leading the technical development of product milestones from refinement of requirements, through execution, operation, and iterating with the broader product development team and partner teams to ensure product success. The impact you will have : Develop systems that make it simple for customers to answer questions about their Databricks environment by providing a reliable and timely interface for observability Make it easy for frameworks teams across Databricks to publish their data to customers Effectively lead large milestones from the observability roadmap, contribute to the long-term vision and requirements development for Databricks products Mentor other engineers towards contributing to the product and the

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role As a Staff Software Engineer on the GTM AI Engineering (Claudification) team, you will build the agents and AI systems that run Anthropic's own go-to-market work. Our sellers already work alongside agents every day. You will take things to the next step and build agents that run complete autonomous motions across areas like inbound, outbound, and pipeline management. In addition, you’ll build eval frameworks that prove those agents are ready for customer-facing work and are driving value. This is a senior role where you’ll drive technical direction for agents and evals across our team. Working closely with sellers, RevOps, and our platform engineering partners, you'll own projects from first prototype through production operation. You'll combine full-stack engineering (MCP servers, agentic systems, web applications, etc.) with hands-on evaluation work (behavior benchmarks, production monitoring, ROI measurement), and help architect the shared platforms that builders from across our go-to-market org contribute to. You've worked in cultures of analytical rigor before, and you're eager to help shape the norms and best practices of a growing AI engineering function at a pivotal moment in the company's growth. Key responsibilities Build and operate autonomous agents that run go-to-market motions end to end, across areas like inbound, outbound, pipeline management, and customer engagement Design the human oversight for each motion: approval gates, handoffs, and escalation paths that keep sellers in control Develop evaluation frameworks for agent behavior, and run them in development and in production Instrument model and tool

Scale is building reliable AI systems for the world’s most important decisions. Our products help leading enterprises, governments, and frontier AI labs build, deploy, and evaluate AI systems at scale. The Orchestration Platform is a core technology used across the company to run durable, reliable, and scalable workflows. It powers the complex, long-running processes behind Scale’s products - from data and model-evaluation pipelines to operational systems and customer-facing workflows. As a Senior Software Engineer, you will help build and evolve this foundational orchestration platform. You will design the primitives, services, and developer experience that enable teams across Scale to author, operate, observe, and safely scale distributed workflows. This is a high-leverage role for an engineer excited by distributed systems, reliability, and platform infrastructure used by many internal teams. You will: Lead the architecture, design, implementation, and operation of Scale’s core orchestration platform. Build durable workflow infrastructure using technologies such as Temporal, Cadence, Kubernetes, and cloud-native systems. Define platform primitives and APIs for scheduling, retries, state management, task execution, observability, and workflow lifecycle management. Partner with product, infrastructure, data, and application teams to understand workflow needs and turn them into reusable platform capabilities. Improve the reliability, scalability, security, and developer experience of services that run critical company workflows. Establish technical standards and best practices for distributed workflow development, deployment, testing, and incident response. Drive cross-functional technical decisions and communicate platform direction clearly to engineers and stakeholders. Ideally, you have: 5+ years of full-time software engineering experience, with a focus on backend, infrastructure, and distributed systems. Experience building and operating production systems with

Scale is building reliable AI systems for the world’s most important decisions. Our products help leading enterprises, governments, and frontier AI labs build, deploy, and evaluate AI systems at scale. The Orchestration Platform is a core technology used across the company to run durable, reliable, and scalable workflows. It powers the complex, long-running processes behind Scale’s products - from data and model-evaluation pipelines to operational systems and customer-facing workflows. As a Senior Software Engineer, you will help build and evolve this foundational orchestration platform. You will design the primitives, services, and developer experience that enable teams across Scale to author, operate, observe, and safely scale distributed workflows. This is a high-leverage role for an engineer excited by distributed systems, reliability, and platform infrastructure used by many internal teams. You will: Lead the architecture, design, implementation, and operation of Scale’s core orchestration platform. Build durable workflow infrastructure using technologies such as Temporal, Cadence, Kubernetes, and cloud-native systems. Define platform primitives and APIs for scheduling, retries, state management, task execution, observability, and workflow lifecycle management. Partner with product, infrastructure, data, and application teams to understand workflow needs and turn them into reusable platform capabilities. Improve the reliability, scalability, security, and developer experience of services that run critical company workflows. Establish technical standards and best practices for distributed workflow development, deployment, testing, and incident response. Drive cross-functional technical decisions and communicate platform direction clearly to engineers and stakeholders. Ideally, you have: 5+ years of full-time software engineering experience, with a focus on backend, infrastructure, and distributed systems. Experience building and operating production systems with