Ai Systems Engineer Jobs

By applying to this role, you will be considered for Research Engineer roles across all teams at OpenAI. About the Role As a Research Engineer here, you will be responsible for building AI systems that can perform previously impossible tasks or achieve unprecedented levels of performance. We're looking for people with solid engineering skills (for example designing, implementing, and improving a massive-scale distributed machine learning system), writing bug-free machine learning code, and building the science behind the algorithms employed. The most outstanding deep learning results are increasingly attained at a massive scale, and these results require engineers who are comfortable working in large distributed systems. We expect engineering to play a key role in most major advances in AI of the future. We expect you to: Have strong programming skills Have experience working in large distributed systems Be excited about OpenAI’s approach to research Nice to have: Interested in and thoughtful about the impacts of AI technology Past experience in creating high-performance implementations of deep learning algorithms About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment

Join the engineering teams that bring OpenAI’s ideas safely to the world!! The Applied Engineering team works across research, engineering, product, and design to bring OpenAI’s technology to consumers and businesses. We seek to learn from deployment and distribute the benefits of AI, while ensuring that this powerful tool is used responsibly and safely. Safety is more important to us than unfettered growth. About the Role As OpenAI continues to grow, we are looking for experienced, problem-solving engineers to ensure our systems scale. Our success depends on our ability to quickly iterate on products while also ensuring that they are performant and reliable. You will work in a deeply iterative, collaborative, fast-paced environment to bring our technology to millions of users around the world, and ensure it’s delivered with safety and reliability in mind. Successful candidates will play a crucial role in ensuring the reliability, scalability, and performance of our systems as we continue to expand. As a reliability expert, you will be at the forefront of maintaining and enhancing the stability, scalability, and performance of our rapidly evolving infrastructure. You will work closely with cross-functional teams, including software engineers, product managers, and data scientists, to build and maintain resilient systems that can handle our growing user base and workload. In this role, you will: Design and implement solutions to ensure the scalability of our infrastructure to meet rapidly increasing demands. Build and maintain the load, chaos and synthetic testing software leveraged by development teams to make the systems they design and operate more reliable. Build and maintain automation tools to streamline repetitive tasks and improve system reliability. Build and maintain the platform for CPU/storage, GPU, and network lifecycle management to drive efficiency, accountability and support dynamic optimization of our resources. Implement fault-tolerant and resilient

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

About the Team Our Robotics team is focused on unlocking general-purpose robotics and advancing toward AGI-level intelligence in dynamic, real-world environments. Working across the full model and systems stack, we integrate cutting-edge hardware and software to explore a broad range of robotic form factors. We strive to seamlessly blend high-level AI capabilities with the physical constraints of real-world systems to improve people’s lives. About the Role We're looking for an experienced Electrical Engineer to help develop the next generation of robotic systems at OpenAI. This role spans the full lifecycle of hardware development, from early concept exploration and prototyping through circuit design, component selection, PCB layout, bring-up, integration, and deployment. Engineers in this role are expected to independently drive significant hardware efforts from initial concept through deployment. You will translate ambiguous goals into concrete engineering plans, make key technical decisions, coordinate closely with cross-functional partners, and own execution through the iterations required to deliver a successful system. Many of the systems we build are still being defined. You will work closely with mechanical, firmware, software, controls, and research teams to evaluate new ideas, develop novel hardware, and integrate it into robotic platforms. Success in this role requires strong engineering judgment, comfort operating in ambiguous spaces, and the ability to balance rapid experimentation with the discipline required to build reliable and scalable systems. The ideal candidate enjoys building things from first principles and is equally comfortable evaluating a new technology, debugging a prototype on the bench, reviewing PCB layout details, and driving system integration efforts. You should be able to move quickly when appropriate, but also know when investing in robustness, simplicity, or infrastructure will create leverage for future development. This role is

About the Team The Privacy Engineering Team at OpenAI is committed to integrating privacy as a foundational element in OpenAI's mission of advancing Artificial General Intelligence (AGI). Our focus is on all OpenAI products and systems handling user data, striving to uphold the highest standards of data privacy and security. We build essential production services, develop novel privacy-preserving techniques, and equip cross-functional engineering and research partners with the necessary tools to ensure responsible data use. Our approach to prioritizing responsible data use is integral to OpenAI's mission of safely introducing AGI that offers widespread benefits. About the Role As a part of the Privacy Engineering Team, you will work on the frontlines of safeguarding user data while ensuring the usability and efficiency of our AI systems. You will help us understand and implement the latest research in privacy-enhancing technologies such as differential privacy, federated learning, and data memorization. Moreover, you will focus on investigating the interaction between privacy and machine learning, developing innovative techniques to improve data anonymization, and preventing model inversion and membership inference attacks. This position is located in San Francisco. Relocation assistance is available. In this role, you will: Design and prototype privacy-preserving machine-learning algorithms (e.g., differential privacy, secure aggregation, federated learning) that can be deployed at OpenAI scale. Measure and strengthen model robustness against privacy attacks such as membership inference, model inversion, and data memorization leaks—balancing utility with provable guarantees. Develop internal libraries, evaluation suites, and documentation that make cutting-edge privacy techniques accessible to engineering and research teams. Lead deep-dive investigations into the privacy–performance trade-offs of large models, publishing insights that inform model-training and prod

About the Team Our Robotics team is focused on unlocking general-purpose robotics and pushing towards AGI-level intelligence in dynamic, real-world settings. Working across the entire model stack, we integrate cutting-edge hardware and software to explore a broad range of robotic form factors. We strive to seamlessly blend high-level AI capabilities with the constraints of physical systems to improve peoples’ lives. About the Role We’re looking for a GPU Inference Engineer to contribute to improvements in model serving efficiency for our Robotics research. This is a high-impact role where you’ll drive initiatives to optimize inference performance and scalability. You’ll also be engaged in model design, to help assist our researchers in developing inference-friendly models. This role is critical to scaling the team’s broader goals - it will directly enable leadership to focus on higher-leverage initiatives by building a stronger technical foundation. In this role you will: Perform engineering efforts focused on improving model serving, inference performance, and system efficiency Drive optimizations from a kernel and data movement perspective to improve system throughput and reliability Partner closely with research and product teams to ensure our models perform effectively at scale Design, build, and improve critical serving infrastructure to support Robotics growth and reliability needs You might thrive in this role if you: Have deep expertise in model performance optimization, particularly at the inference layer Have a strong background in kernel-level systems, data movement, and low-level performance tuning Are excited about scaling high-performing AI systems that serve real-world, multimodal workloads Can navigate ambiguity, set technical direction, and drive complex initiatives to completion 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. About OpenAI OpenAI i

About the Team The Connectivity Software Engineering team is responsible for enabling seamless, secure, and high-performance wireless connectivity across OpenAI’s products. We design and optimize Bluetooth, BLE, Wi-Fi, and emerging wireless technologies to ensure robust device pairing, network performance, and interoperability. Our work spans kernel drivers, system services, and user-level tools, with a focus on real-world performance, scalability, and reliability. About the Role OpenAI is seeking a Connectivity Software Engineer to design, implement, and optimize wireless connectivity features across our product ecosystem. You’ll work at the intersection of systems software, wireless standards, and hardware integration—building robust pairing and provisioning flows, debugging low-level protocols, and driving performance under real-world RF constraints. You will also support certification, field interoperability, and fleet-scale connectivity infrastructure. This role is based in San Francisco, CA . We use a hybrid work model of 4 days in the office per week and offer relocation assistance to new employees. In this role, you will: Design, implement, and debug Bluetooth/BLE and Wi-Fi features across kernel drivers, BlueZ/wpa_supplicant/hostapd, and systemd/D-Bus services Deliver robust pairing, bonding, and provisioning flows (GATT/GAP, LE Audio/LC3, WPA3/802.1X, captive portals, NAN) Optimize link performance: throughput, latency, jitter, roaming, coexistence (BT↔Wi-Fi), and power modes (TWT, WoWLAN) Build reliable network management using NetworkManager/nmcli, nl80211/cfg80211/mac80211, DNS/DHCP/mDNS, P2P/SoftAP Instrument and analyze with packet captures and tooling (btmon/hcidump, Wireshark, iperf, eBPF/perf, spectrum sniffers) Drive interoperability and certification readiness (Bluetooth SIG, Wi-Fi Alliance) and resolve field issues with root-cause fixes Contribute to OTA-safe configuration, telemetry, and diagnostics for fleet-scale operation You might thrive in

About the Role: We're hiring Senior and Staff Data Platform Engineers to join the Data Infrastructure teams in Toronto. Together these teams own the infrastructure that processes billions of events per day: Spark-on-Kubernetes, Flink and Kinesis pipelines, a multi-petabyte Delta Lake, a large-scale MemoryDB feature store, Databricks multi-environment operations, and the catalog and lifecycle systems that govern it. The team is small and senior. Each engineer owns major platform components: you design it, build it, and support it in production. This is a hybrid-role based out of our Toronto office. You must be willing to travel to our Toronto office two days/week. What You'll Do: Spark-on-Kubernetes — EKS-based compute platform for Spark workloads: cluster configuration, Pod Identity IAM, job environment setup, Kustomize overlays, and shadow canary validation Event ingestion — Rust services and Flink jobs processing billions of events per day over Kinesis; throughput, reliability, on-call response, and AI-assisted operational tooling to reduce toil Platform infrastructure — Terraform modules for environment provisioning, cross-account AWS IAM, ARC runner infrastructure, and CI/CD for data platform changes Feature store and ML compute — Flink-based real-time feature pipelines feeding a large-scale MemoryDB cluster; GPU capacity governance and Databricks multi-environment operations for ML training workloads Workflow orchestration and CDC — Airflow-based DAG deployment, change data capture pipeline operations, and data quality monitoring Your Background: 3+ years building and operating production data platform infrastructure at the cluster or platform level, across Spark, Flink, Kinesis, Kubernetes, or equivalent Deep experience in at least one of: Spark-on-K8s cluster operations, Rust-based data or systems engineering, Kubernetes platform engineering and IaC, or data catalog and governance tooling Production AWS experience or equivalent: EKS, S3, Kinesis, and mu

Your wellbeing, our mission. Join a company shaping a healthier world. GET TO KNOW US At Wellhub we're revolutionizing workplace wellness. Our platform connects employees worldwide to the best partners for fitness, mindfulness, therapy, nutrition, and sleep—all in one simple subscription. Headquartered in NYC with team members in Europe, North America and South America, we’re on a mission to make every company a wellness company. We believe work should be fulfilling, inspiring, and balanced. Here, you’ll find a team that values wellbeing, collaboration, and different perspectives, where passion and creativity push boundaries to create real impact. Your contributions will help shape a healthier, more balanced world for you and millions of people globally. Join us in redefining the future of wellbeing! THE OPPORTUNITY We are hiring a Cloud Security Engineer for the InfoSec team in Brazil ! We are looking for an experienced security engineer to lead our cloud security strategy across multi-cloud environments (AWS & GCP). You will drive our Zero Trust architecture, embed a Shift-Left security culture within engineering teams, secure containerized and serverless workloads, and pioneer security controls for emerging Artificial Intelligence deployments—including Agentic AI systems, Model Context Protocol (MCP), Retrieval-Augmented Generation (RAG) architectures, AI guardrails, and mitigations against OWASP Top 10 for LLMs and MITRE ATLAS framework threats. This position is for the Cloud Security team. The Cloud Security Engineer is responsible for designing, implementing, and managing security measures in cloud computing environments to protect data, applications, infrastructure, and services against potential threats and vulnerabilities. YOUR IMPACT Architect and govern cloud security controls across AWS and GCP environments following Zero Trust principles; Embed automated security testing and threat modeling directly into CI/CD pipelines to champi

At Affirm, we exist for the moments that matter—giving people a clear, predictable way to pay over time, with no hidden fees, no surprises, and no tradeoffs on what matters most. We’re looking for a curious, driven professional to join our Revenue Analytics team. This builds and owns the data products, reporting infrastructure, semantic foundations, and analytical systems that power Affirm’s Revenue organization. As a Analyst at Revenue Analytics, you’ll build scalable data products that power day-to-day decision-making - owning end-to-end work across data modeling, metric definitions, dashboards, automation, and enablement. You’ll also help strengthen our semantic layer and data governance, laying the foundation for reliable AI. The ideal candidate combines strong technical and analytical skills with the ability to turn ambiguous business questions into durable, well-tested data infrastructure. What you'll do Develop dbt data models, dashboards, metrics, and automation processes for the revenue field team and revenue analysts Build and maintain critical reporting data models that power external merchant reporting Build the semantic, metadata, and context layers that allow AI systems to accurately understand Revenue data, metrics, and business definitions Partner with Business Systems, engineering, and business stakeholders to translate requirements into durable, well-tested data products Contribute to the team’s best practices in version control, code review, documentation, and release hygiene (GitHub-based workflows) Develop processes, governance, and foundations to scale the impact of analytics within Revenue. What we look for 3+ years of work experience in an analytics engineering or business intelligence role Strong working knowledge of SQL, dbt, Python, data modeling, and data visualization Hands-on experience with BI tools (Sigma/Looker/Tableau), Databricks, and cloud data warehouses (Snowflake) Understanding of the data founda

At Affirm, we exist for the moments that matter—giving people a clear, predictable way to pay over time, with no hidden fees, no surprises, and no tradeoffs on what matters most. We’re looking for a curious, driven professional to join our Revenue Analytics team. This builds and owns the data products, reporting infrastructure, semantic foundations, and analytical systems that power Affirm’s Revenue organization. As a Senior Analyst, Revenue Analytics, you’ll build scalable data products that power day-to-day decision-making - owning end-to-end work across data modeling, metric definitions, dashboards, automation, and enablement. You’ll also help strengthen our semantic layer and data governance, laying the foundation for reliable AI. The ideal candidate combines strong technical and analytical skills with the ability to turn ambiguous business questions into durable, well-tested data infrastructure. What you'll do Develop dbt data models, dashboards, metrics, and automation processes for the revenue field team and revenue analysts Build and maintain critical reporting data models that power external merchant reporting Build the semantic, metadata, and context layers that allow AI systems to accurately understand Revenue data, metrics, and business definitions Partner with Business Systems, engineering, and business stakeholders to translate requirements into durable, well-tested data products Contribute to the team’s best practices in version control, code review, documentation, and release hygiene (GitHub-based workflows) Develop processes, governance, and foundations to scale the impact of analytics within Revenue. What we look for 3+ years of work experience in an analytics engineering or business intelligence role Strong working knowledge of SQL, dbt, Python, data modeling, and data visualization Hands-on experience with BI tools (Sigma/Looker/Tableau), Databricks, and cloud data warehouses (Snowflake) Understanding of the data f

OUR MISSION At Redwood, we empower our customers with lights-out automation for their mission-critical business processes. ABOUT US Redwood Software is the leading orchestration platform for the autonomous enterprise, driving business transformation at the lowest total cost of ownership. Redwood empowers organizations to intelligently automate and orchestrate mission-critical business and IT processes across complex ERP, hybrid cloud, data and emerging agentic AI systems. Through its SaaS-first automation fabric—with AI embedded across the automation lifecycle—Redwood accelerates the path to autonomous operations. Backed by 30 years of experience and trusted by more than 50% of the Fortune 50, Redwood helps organizations unlock human potential to focus on innovation, growth and what’s next. CORE VALUES One Team. One Redwood Make Your Own Weather Obsess over Customer Success Work the Problem Be Curious Own the Outcome Respect Each Other YOUR IMPACT We are looking for a Software Engineer, Platform & Integrations . Working closely with senior and lead engineers, you will design, develop, and maintain high-quality features that power enterprise data exchange for more than 1,000 customers worldwide. This is an incredible opportunity to deepen your expertise in cloud-native architectures, enterprise security, and modern DevOps practices in a fast-growing product environment. Feature Development & Design: Write clean, maintainable, and well-tested code using Java and Spring Boot to deliver scalable backend services and microservices. Platform Reliability: Contribute to enhancing the monitoring, logging, and observability of our core platform to ensure high availability and performance. Security & Compliance: Implement secure coding practices to safeguard data exchange and maintain compliance across our cloud infrastructure. Collaborative Execution: Work within an agile team, collaborating closely with QA, Product, and fellow engineers to deliver high-qual

MongoDB Technical Services Engineers use their exceptional problem solving and customer service skills, along with their deep technical experience, to advise customers and to solve their complex MongoDB problems. Technical Service Engineers are experts in the entire MongoDB ecosystem - database server, drivers, cloud, and infrastructure. This also includes services such as Atlas (database as a service), or Cloud Manager (which helps customers with automation, backup and monitoring of their MongoDB systems). Our engineers combine their MongoDB expertise with passion, initiative, teamwork, and a great sense of humor to help our customers be successful with MongoDB. The position will be based in our Gurugram office. The standard work week will be Monday to Friday, every week. We are looking to speak to candidates who are based in Gurugram for our hybrid working model. Cool things you’ll do You'll be working alongside our largest customers, solving their complex challenges - resolving questions on architecture, performance, recovery, security, and everything in between. You'll be an expert resource on best practices in running MongoDB at scale, whatever that scale may be. You'll be an advocate for customers' needs - interfacing with our product management and development teams on their behalf. And you'll contribute to internal projects, including software development of support tools for performance, benchmarking, and diagnostics. What you need You should have 5+ years of proven experience, we consider all candidates with an eye for those who are self-taught, insatiably curious, and multi-faceted. The ideal candidates should have strong technical experience in more than one of the following areas Systems engineering experience, including Linux performance, memory management, I/O tuning, configuration, security, networking, clusters, and troubleshooting Understand core Kubernetes concepts, including containers, namespaces, custom resources and multi-cluster dep

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 Container runtimes were designed for general-purpose software workloads. AI inference is not a general-purpose workload. Running large models at production scale exposes cracks in every layer of the container stack: runtimes unaware of GPU memory constraints, images that take minutes to pull when a model needs to scale to thousands of replicas, and isolation mechanisms that weren't designed for the multi-tenant serving environments that production AI requires. The tools the industry has relied on for a decade weren't built for this, and patching around those limitations at higher layers only goes so far. Baseten owns the entire pipeline, from the moment a developer pushes a model to the moment a request gets a response. That vertical ownership means we can fix these problems at the root. The Runtime Fabrics team is doing exactly that: purpose-building the container runtime and storage layers for AI inference workloads, led by some of the world's top containerd maintainers. As Engineering Manager of the Runtime Fabrics team, you will lead this work, setting technical direction, growing a world-class team of systems engineers, and ensuring the team's output shapes not just Baseten's infrastructure but the open-source container ecosystem at large. If you've contributed to containerd, runc, or related OCI projects and are ready to lead a team solving some of the hardest problems in infrastructure today, we'd love

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 As an Engineering Manager (Player & Coach), you will lead and mentor a team of Forward Deployed Engineers focused on building, scaling, and optimizing LLM inference workloads for Baseten customers. Applying both hands-on technical ownership and managerial leadership, you will guide your team through the processes of designing, deploying, and managing high performance, low latency AI applications on Baseten’s platform. FDE at Baseten is not a sales function – we are a mix of engineering, product, and customer architects who contribute to the core Baseten codebase, drive large portions of our feature roadmap, and execute on complicated customer engagements. You will also partner with product, infrastructure, and other customer engineering teams to ensure that large language models (LLMs) and other generative AI systems deliver best-in-class performance, reliability, and cost efficiency in production environments. EXAMPLE INITIATIVES Take a look at these blog posts written by members of our Forward Deployed Engineering team: Forward Deployed Engineering on the frontier of AI The fastest, most accurate Whisper transcription Deploy production-ready model servers from Docker images Deploy custom ComfyUI workflows as APIs RESPONSIBILITIES Leadership & Team Management Lead, mentor, and grow a team of Forward Deployed Engineers, providing guidance on technical direction, project execution, and professional deve