Senior Software Engineering Manager 2c Engine Ui in United States

Every day, tens of millions of people come to Roblox to explore, create, play, learn, and connect with friends in 3D immersive digital experiences– all created by our global community of developers and creators. At Roblox, we’re building the tools and platform that empower our community to bring any experience that they can imagine to life. Our vision is to reimagine the way people come together, from anywhere in the world, and on any device. We’re on a mission to connect a billion people with optimism and civility, and looking for amazing talent to help us get there. A career at Roblox means you’ll be working to shape the future of human interaction, solving unique technical challenges at scale, and helping to create safer, more civil shared experiences for everyone. The Security organization at Roblox is responsible for designing and engineering secure systems from inception through production. We define security standards, build scalable controls, and enable product and infrastructure teams to operate securely by default. The Application Security team partners closely with engineering teams early in the development lifecycle to drive secure architectures, establish standards, and deliver scalable security solutions. As a Senior Security Software Engineer - Application Security , you will be a hands-on engineer who designs, builds, and ships security solutions that integrate directly into developer workflows and platforms. You will play a key role in scaling application security through automation, CI/CD integrations, secure libraries, and reusable patterns. In this role, you will help define how security is embedded across the software development lifecycle at Roblox, balancing deep technical work (threat modeling, code review, penetration testing) with systemic solutions that reduce risk at scale. You will also participate in AppSec on-call rotations and contribute to security tooling and platform evolution. You will: Integrate security into CI/CD pi

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. Build the future of data. Join the Snowflake team. The Snowflake Machine Learning Platform team’s mission is to enable customers to bring their machine learning and deep learning workloads to Snowflake. Our customers want to build powerful models with the ever-increasing data in Snowflake but face several challenges including infrastructure optimizations, orchestration, performance, and security. The team aims to solve these challenges by building highly integrated platform solutions that are simple, secure, and enable end-to-end ML workflows. We are on an early journey to build the most scalable machine learning and data platform without sacrificing the benefits of a single platform and governance. We are looking for outstanding technical leaders who will join our ML Platform team to build the next-generation platform and play a pivotal role in this journey by understanding Snowflake’s core platform architecture and evolving it to enable state-of-the-art machine learning and LLM workloads. Join us to define strategies, set technical directions, design and execute, engage and deliver innovation, and unlock the power of AI for thousands of enterprise customers. This position is based in Menlo Park, CA, and Bellevue, WA. RESPONSIBILITIES : Help define and own the roadmap, wor

About the Team 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 We’re seeking Software Engineers who can solve complex, high-impact problems across our stack. In this role, you’ll join a nimble team driving the deployment of OpenAI’s technology into new environments and infrastructure that power critical missions in the public sector. You’ll work cross-functionally with product, security, and compliance teams to build the functionality needed to deliver a scalable, reliable platform. You’ll also partner directly with customers to design and build new products and features that create real-world impact. From launching net-new capabilities to optimizing how we serve inference in unique, high-stakes environments, this role offers both breadth and technical depth—giving you the opportunity to shape the future of OpenAI’s technology where it matters most. This role is based in Washington D.C., San Francisco, CA or Seattle, WA. Occasional travel to customer sites is required for this role. In this role, you will: Own the development of new customer-facing ChatGPT and OpenAI API features end-to-end, both on-premises and in the cloud, for our public sector customers. Partner and directly embed with teams across the business, including engineering, security, and compliance, to enable our products to work within the unique constraints of new environments. Talk to users to understand their problems and design solutions to address them Work with the research team to get relevant feedback and iterate on their latest models, developing solutions specific for public sector customers at both the model & data

Join the NVIDIA's Solutions Engineering team that is reshaping the future of driving! Our goal is to build and deploy scalable solutions for autonomous vehicles and as a result, create safer and more efficient roads. Our team is hands-on, passionate about practical results, and values diversity. You will help craft the application software architecture by working closely with external partners developing on our platform and on collaborations across multiple teams within NVIDIA working on autonomous vehicles. You will also advance and refine the overall drivability of our solution, focusing on integration challenges and using your deep analytical skills to tease through the complexity of the system to find effective solutions. NVIDIA is widely considered to be one of the technology world’s most desirable employers, and is committed to fostering a diverse work environment and proud to be an equal opportunity employer. If you are passionate in bringing autonomous vehicles into the world and see the solution come together, we would like to hear from you! What you'll be doing: Shape the application architecture internally, with a focus on perception & sensor fusion, by collaborating closely with architecture and software development teams. Integrate and adapt NVIDIA solutions in target vehicles, ensuring that both perception and sensor fusion are adapted and tuned to meet the desired driving performance and functionality. Lead bring-up activities and provide technical support to resolve functional and perception & sensor fusion related issues. Perform and leverage in-vehicle and simulation test drives for functional and performance analysis on the recorded data. Work with our partners to efficiently integrate hardware and software components, understand the system architecture, profile performance, identify bottlenecks, and drive optimization <

We are looking for a Senior System Software Engineer, Software Defined Networking to design, build, and operate highly performant and scalable SDN solutions for NVIDIA's AI Clouds hosting GPU-accelerated workloads — including hyperscale multi-node training, inference, cloud gaming, and cloud functions. This role spans the full lifecycle of our SDN stack — from designing and developing new control and data plane software to ensuring operational excellence in production through reliability engineering, CI/CD, observability, and incident response. What you'll be doing: Design and develop next-generation multi-tenant cloud SDN control and data plane software (OVS, OVN, OpenFlow) Build Infrastructure-as-a-Service virtual network orchestration and services using gRPC and REST to support tenant workload security and performance SLAs for BMaaS, VMaaS, and Kubernetes Drive upstream contributions to OVN-Kubernetes and related open-source projects Develop software for network observability — monitoring, telemetry, intelligent metering, and performance analysis Operate and support OVS-OVN based SDN solutions in large-scale NVIDIA AI Cloud environments Own end-to-end observability for the SDN stack — build and maintain monitoring, alerting, distributed tracing, and dashboarding to ensure real-time insight into network health, performance, and tenant SLAs Design, enhance, and maintain CI/CD pipelines (GitLab) across Linux host networking, OVS, OVN, and Kubernetes CNIs Implement GitOps approaches or related experience for secure, seamless integration with cloud infrastructure Drive reliability through incident management, resource monitoring, and performance tuning<

About Datadog: We're on a mission to build the best platform in the world for engineers to understand and scale their systems, applications, and teams. We operate at high scale—trillions of data points per day—providing always-on alerting, metrics visualization, logs, and application tracing for tens of thousands of companies. Our engineering culture values pragmatism, honesty, and simplicity to solve hard problems the right way. The Opportunity: Datadog’s Senior Staff Engineers are technical leaders operating at the forefront of large-scale systems design, building the infrastructure that will support our next five years of growth and beyond. They do this in three major ways: As individual contributors, they bring world-class technical depth to build industry-leading systems in areas such as observability data platforms, distributed query engines, and real-time event streaming at global scale. As technical leaders, they apply broad architectural perspective and deep systems thinking to align design decisions across teams and domains. They work across complex, multi-team problem spaces to define long-term technical direction, drive large-scale initiatives forward, and ensure consistent execution. As engineering stewards, they play a key role in evolving our systems and engineering culture. They actively participate in Datadog’s senior technical community, bringing external insights and internal experience to elevate engineering standards and mentor the next generation of technical leaders. Examples of projects a Senior Staff Engineer may lead include designing and launching a new distributed data storage engine capable of handling hundreds of millions of records per second, building the real-time infrastructure behind a new observability product, or re-architecting a core service to support exponential growth in throughput and complexity. What You’ll Do: Be the technical owner of multiple critical systems or architecture areas, often spanning several t

About Pinecone Pinecone is the knowledge infrastructure for AI at scale. Its leading vector database and knowledge engine, Pinecone Nexus, power accurate, performant AI applications for more than 9,000 customers and 800,000 developers worldwide. Pinecone's mission is to make AI knowledgeable. Pinecone is based in New York and raised $138M in funding from Andreessen Horowitz, ICONIQ, Menlo Ventures, and Wing Venture Capital. About the Team and Role: The Experience team is at the center of one of the most exciting transitions in software development history — the shift from human-driven to agent-driven product experiences. We own Pinecone's API, clients, authentication, revenue, and observability systems, and right now that means redesigning all of it for a world where AI agents are first-class users alongside humans. This is a wide-scope role. You'll own things end-to-end — from backend architecture to API design to SDK and web surfaces. You’ll be working closely with product, design, and other engineering teams to identify user needs and build the right thing, at the right abstraction level, at the right time. Along the way, you will be building high-leverage platform capabilities that accelerate Pinecone’s product development and user growth systems. We're looking for an engineer who sees this moment for what it is: a rare opportunity to shape how developers and agents interact with a category-defining product. You're not waiting to see how the industry figures out MCP, agentic workflows, and AI-native interfaces — you're already experimenting, already forming opinions, already building. You know that speed and leverage matter more than labor, and you've internalized AI-assisted development not as a productivity trick but as a fundamentally different way of working. Responsibilities: Pioneer our agent experience. Shape how AI agents interact with Pinecone — designing interfaces, protocols (MCP), and tooling that make Pinecone the easiest and most capable platform f

About Pinecone Pinecone is the knowledge infrastructure for AI at scale. Its leading vector database and knowledge engine, Pinecone Nexus, power accurate, performant AI applications for more than 9,000 customers and 800,000 developers worldwide. Pinecone's mission is to make AI knowledgeable. Pinecone is based in New York and raised $138M in funding from Andreessen Horowitz, ICONIQ, Menlo Ventures, and Wing Venture Capital. About the Team and Role: The Experience team is at the center of one of the most exciting transitions in software development history — the shift from human-driven to agent-driven product experiences. We own Pinecone's API, clients, authentication, revenue, and observability systems, and right now that means redesigning all of it for a world where AI agents are first-class users alongside humans. This is a wide-scope role. You'll own things end-to-end — from backend architecture to API design to SDK and web surfaces. You’ll be working closely with product, design, and other engineering teams to identify user needs and build the right thing, at the right abstraction level, at the right time. Along the way, you will be building high-leverage platform capabilities that accelerate Pinecone’s product development and user growth systems. We're looking for an engineer who sees this moment for what it is: a rare opportunity to shape how developers and agents interact with a category-defining product. You're not waiting to see how the industry figures out MCP, agentic workflows, and AI-native interfaces — you're already experimenting, already forming opinions, already building. You know that speed and leverage matter more than labor, and you've internalized AI-assisted development not as a productivity trick but as a fundamentally different way of working. Responsibilities: Pioneer our agent experience. Shape how AI agents interact with Pinecone — designing interfaces, protocols (MCP), and tooling that make Pinecone the easiest and most capable platform f

We’re looking for a Senior Staff Software Engineer with deep experience in GenAI/ML to join Datadog’s Application Performance Monitoring (APM) team. APM is a product which provides deep visibility into applications, enabling users to identify performance bottlenecks, troubleshoot issues, and optimize services. With distributed tracing, profiling, out-of-the-box dashboards, and seamless correlation with other telemetry data, Datadog APM provides some of the deepest and most structured visibility into the health and performance of applications. This context sets us up for an opportunity to be the world leaders in agentic investigations and incident troubleshooting. You’ll act as a technical leader within the APM group, focused on agentic workflows. You’ll lead efforts to design, train, evaluate, and deploy GenAI/ML models at scale. We’re looking for a product-minded ML engineer with strong technical expertise, excellent communication skills, and a track record of driving impactful initiatives end to end. At Datadog, we place value in our office culture - the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You’ll Do: Serve as the technical owner for GenAI initiatives within APM, leading design, development, and deployment of ML/AI-powered features across multiple teams. Guide long-term strategy and technical direction for GenAI workflows across APM and related products. Build and benchmark GenAI/ML models using state-of-the-art techniques. Contribute to Datadog’s broader senior engineering community through thought leadership and collaboration on company-wide initiatives. Collaborate with cross-functional teams to build automated investigation and triaging tools. Influence product direction by bringing a strong product mindset to your work, always advocating for the end user. Guide teams through ambiguity, sc

NVIDIA is a leading artificial intelligence computing company, and we are paving the way with innovations in self-driving cars, machine learning, supercomputing, gaming, and visualization. We give automakers, tier-1 suppliers, automotive research institutions, and start-ups the power and flexibility to develop and deploy breakthrough artificial intelligence systems for self-driving vehicles. Our unified computing architecture enables training deep neural networks in the data center, and then seamlessly runs them on NVIDIA DRIVE Platforms inside the vehicle. The Hypervisor and RTOS Team within NVIDIA DRIVE Software plays a critical role in NVIDIA's expansion into the world of artificial intelligence and autonomous vehicles. Our job is to facilitate the sharing and separation of system resources while achieving real-time, safety, and security requirements. We develop Hypervisor and RTOS with a strong focus on automotive quality, safety and security needed for the real-time, highly available system level components of world-class Autonomous Vehicles. We are making extensive use of formal methods to automate our workflow and increase the quality of our SW. We are hiring now for the position of Senior System Software Engineer for Hypervisor and RTOS What you’ll be doing: Design and develop new features for RTOS and hypervisor software stack. Bring up and optimize RTOS and hypervisor stacks on new NVIDIA Tegra SoCs. Develop high-integrity software using best-in-class engineering, safety, and security practices. Debug complex system-level issues across hardware, firmware, RTOS, and virtualization layers. Lead team-wide technical initiatives by building alignment, coordinating execution, and driving them to completion. What we need to see: BS, MS in CS/CE/EE or a related engineering field or equivalent experience </

Mid-Level or Senior Aerospace Systems Safety Engineer Company: The Boeing Company The Boeing Defense Air Dominance Division Systems Safety & Mission Assurance organization is looking for an Aerospace Systems Safety Engineer to join our team in Hazelwood, MO . Our teams are currently hiring for a broad range of experience levels including Experienced (Level 3) or Senior (Level 4) Aircraft Safety Engineers. A successful candidate will perform system software safety engineering work on a Proprietary Air Dominance program, drive hazard analyses, demonstrate compliance to MIL‑STD‑882E and other standards, and influence system architecture to reduce safety risk. The selected candidate will provide technical guidance and perform critical Software System Safety Engineering work. In addition to working with System Safety personnel, the individual will work extensively with design, development, and test to incorporate robust safety features and reduce project safety risk. Primary responsibilities: Analyzes the integration of complex airplane systems and their corresponding airplane-level effects, failure indications, and flight crew actions as part of a system of systems analysis Documents safety analyses, hazard mitigation, validation, and verification activities in compliance with relevant customer and regulatory safety standards such as MIL-STD-882E, MIL-HDBK-516C, AC-17-01, DO-178C, and DO-254. Demonstrates safety hazard risk mitigation and control methods to the customer and regulators Identifies safety issue systemic root causes and recommends corrective actions using industry best practices Collaborates with internal and external stakeholders to define, validate, and inte

This is a senior individual contributor role for someone who wants to actively shape how Engineering, one of the most important parts of how Datadog develops its people. You'll sit at the center of Datadog's biggest talent bets for Engineering: how we build leaders, define career paths and org design, evolve performance, move talent internally, and plan succession for our most critical roles. You’ll own this work end to end, from the first framing conversation with senior leaders through to delivering a program running at scale. AI is changing how Engineering builds software, and it is changing how People builds the programs that support Engineering too. This role sits at the centre of both: understanding how AI is reshaping engineering roles, skills and structures, and building AI-powered solutions within People to keep pace. At Datadog, we place value in our office culture - the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You’ll Do: Design and lead complex talent programmes for Engineering, spanning leadership capability, career architecture, org design, performance, internal mobility and succession for critical roles. Partner directly with PBPs and senior leaders to turn ambiguous problems into clear programme goals, design principles and success measures. Help Engineering and People understand and respond to how AI is reshaping roles, skills and ways of working, and translate that shift into practical talent and org design choices. Stay hands-on from concept through to adoption: this is a build and run role, not a strategy and handover role. Work across Enablement, Learning, People Analytics and People Systems so what you build scales and embeds into core people processes. Equip PBPs with frameworks, tools and executive-ready narratives that support real adoption in the business. Operate in ambiguity and influe

We are investing in agentic AI and need a Senior AI Engineer to lead the design and delivery of these systems. This is a foundational hire: you will own both the agent-facing workstreams — pipelines, orchestration, conversational interfaces — and the underlying context layer that makes them reliable, including memory management, knowledge graph integration, and retrieval infrastructure. You will work closely with data engineers, project leads, and client stakeholders, and play a key role in shaping how Lynx builds and ships AI solutions at scale. What This Involves: Lead the architecture and delivery of agentic AI systems end-to-end: agents, orchestration, tool use, and multi-step reasoning workflows. Own the context layer: design and implement memory architectures (episodic, semantic, working memory) and integrate GraphRAG and knowledge graph retrieval into agentic pipelines. Build robust RAG systems — including vector retrieval, graph traversal, and hybrid search — and ensure retrieval quality through evaluation frameworks. Translate client requirements into technical designs, presenting approaches and trade-offs to both technical and non-technical stakeholders. Define standards and reusable patterns for agentic AI development that other engineers at Lynx can build on. Set up observability, evaluation, and monitoring pipelines to ensure AI systems perform correctly in production. Requirements: 5–8 years of software or ML engineering experience, with at least 2–3 years building LLM-based or agentic AI systems in production. Deep hands-on experience with agentic frameworks (LangChain, LlamaIndex, AutoGen, CrewAI, or similar) and LLM APIs (OpenAI, Anthropic, etc.). Strong understanding of agent design patterns: ReAct, planning loops, tool use, multi-agent coordination, and memory architectures. Practical experience with GraphRAG or knowledge graph-based retrieval (e.g., Neo4j, Microsoft GraphRAG) and vector databases (Pinecone, Weaviate, Qdrant, etc.). Proficiency in

GitLab is the intelligent orchestration platform for DevSecOps. GitLab enables organizations to increase developer productivity, improve operational efficiency, reduce security and compliance risk, and accelerate digital transformation. More than 50 million registered users and more than 50% of the Fortune 100* trust GitLab to ship better, more secure software faster. The same principles built into our products are reflected in how our team works: we embrace AI as a core productivity multiplier, with all team members expected to incorporate AI into their daily workflows to drive efficiency, innovation, and impact. GitLab is where careers accelerate, innovation flourishes, and every voice is valued. Our high-performance culture is driven by our values and continuous knowledge exchange, enabling our team members to reach their full potential while collaborating with industry leaders to solve complex problems. Co-create the future with us as we build technology that transforms how the world develops software. * Fortune 500® is a registered trademark of Fortune Media IP Limited, used under license. Claim based on GitLab data. Fortune 100 refers to the top 20% ranked companies in the 2025 Fortune 500 list, published in June 2025. Fortune and Fortune Media IP Limited are not affiliated with, and do not endorse products or services of GitLab. An overview of this role As a Senior Backend Engineer on GitLab's Nonlinear Productivity team, you'll find and remove friction across the software development lifecycle using reliable AI-powered automation — diagnosing problems like long review cycles, manual release steps, and brittle automation, then building the automation and process changes that resolve them for good. Some examples of the problems this team takes on: Cutting the time it takes to complete a good code review — one that still keeps a human in the loop — by half, using agentic solutions. Turning a manual, error-prone release step into an agentic workflow that ca

About the Team The Privacy Engineering team builds the systems and technical foundations that govern how user data is understood, retained, accessed, and used across OpenAI. We partner with Product, Data, Infrastructure, Security, and Legal to translate policy and trust commitments into durable architecture and enforceable controls. Our work spans data inventory and mapping, classification and lineage, retention and deletion, access governance, purpose and usage controls, auditability, and lifecycle automation. We aim to make policy-aligned data handling the default while giving teams clear, reliable primitives for building and operating products at scale. About the Role We are looking for an experienced Software Engineer to drive the architecture and execution of user data governance across OpenAI. You will define technical direction, build shared platforms and controls, and lead cross-functional programs that make data flows discoverable, policies enforceable, and ownership explicit. This role is well suited to a senior engineer who can move between deep systems design and organization-wide influence, turn ambiguous requirements into pragmatic roadmaps, and operate high-trust systems end to end. This position is based in San Francisco. Relocation assistance is available. In this role, you will: Set the technical strategy and architecture for user data governance across data mapping, classification, lineage, retention, deletion, access, and permitted usage. Design and build shared services, APIs, metadata systems, and policy-enforcement mechanisms that make governance controls consistent, scalable, and auditable. Establish reliable inventories of user data, system ownership, data flows, and policy applicability across products, infrastructure, analytics, and research systems. Partner with Product, Data, Infrastructure, Security, and Legal leaders to define decision rights, translate requirements into controls, and drive adoption across teams. Own governance systems