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Senior Engineer 2c Process Control System Jobs

7,101 active opportunities · Updated for October 2026

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Explore current senior engineer 2c process control system jobs. Use filters to narrow by work mode, employment type, experience and date posted.

V
1mo ago

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. Our Senior Software Engineers lead and mentor engineers, delivering high-value products for our customers and infrastructure that enables our business to scale. Vanta’s product monitors the security posture for thousands of companies, pulling tens of millions of API calls of data per day, pushing information from hundreds of thousands of laptop agents, and running tests against that data continuously to identify potential security threats. Our infrastructure and tooling need to stay ahead of exponential growth in our customer base. As a Senior Software Engineer at Vanta, you’ll be responsible for setting technical direction to provide a strong foundation for our infrastructure to scale with our business. You will also drive complex projects across our technical stack and mentor our talented engineering team. Your past experience will be leveraged to enable and accelerate Vanta’s growth. Visit our Vanta Engineering Blog to learn more about what our team is working on! What you’ll do as a Senior Software Engineer on the Identity team at Vanta: As Vanta expands its agentic capabilities across surfaces like MCP, CLI, and the Vanta Agent, the Identity team is at the center of a new set of problems: defining what it means for an agent to act as a user's proxy, enforcing consistent permission checks across every invocation surface, and building an attribution model that makes agent-assisted actions auditable and trustworthy. You'll help design the identity primitives that make autonomous agent behavior safe and governable at scale. You will also: Lead complex projects with multiple stakeholders and engineers to enable our business and

restaigo
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N
Nuro
📍 Mountain View• Full-time• From $193.9K/yr
1mo ago

Who We Are Nuro believes self-driving vehicles are the most immediate and profound opportunity for AI to drive positive change in the physical world. Safer streets, more time for what matters, and easier access to the world around us, that’s why we’re building a universal autonomy platform: self-driving for all roads and all rides. Founded in 2016, Nuro is a physical AI company developing Level 4 autonomous driving technology for a wide range of vehicles, use cases, and markets. Powered by the Nuro Driver™, our universal autonomy platform enables the global mobility ecosystem to deploy autonomy at scale, from robotaxis and logistics fleets to personal vehicles. With years of real-world deployment experience and a flexible, partner-led business model, Nuro is working toward a future where millions of autonomous vehicles powered by our technology help make everyday life safer, easier, and more connected. Nuro has raised over $2B in capital from Uber, NVIDIA, Google, Softbank, Fidelity, T. Rowe Price, and other leading investors. About the Role Our software team is growing, and we are looking for talented engineers to join us and be instrumental to one of the following areas: Onboard Systems, Performance, and Devices Platform. Onboard Systems: Our onboard system team’s software engineers provide a reliable and high-performance platform that allows our autonomy teams to integrate their autonomy software and algorithms that work across various self-driving platforms. This work requires close collaboration with our software teams, hardware teams, and systems/safety team to make sure new software and hardware work together safely and reliably, and resolve onboard error and performance problems. Performance: Our Performance team optimizes the performance of Nuro’s AV software, ensuring our vehicles can react quickly and safely to the world around them. The team builds systems and tools for continuous performance analysis, and drives latency reduction and resource efficiency

pythonreactai
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N
Nuro
📍 Mountain View• Full-time• From $193.9K/yr
1mo ago

Who We Are Nuro believes self-driving vehicles are the most immediate and profound opportunity for AI to drive positive change in the physical world. Safer streets, more time for what matters, and easier access to the world around us, that’s why we’re building a universal autonomy platform: self-driving for all roads and all rides. Founded in 2016, Nuro is a physical AI company developing Level 4 autonomous driving technology for a wide range of vehicles, use cases, and markets. Powered by the Nuro Driver™, our universal autonomy platform enables the global mobility ecosystem to deploy autonomy at scale, from robotaxis and logistics fleets to personal vehicles. With years of real-world deployment experience and a flexible, partner-led business model, Nuro is working toward a future where millions of autonomous vehicles powered by our technology help make everyday life safer, easier, and more connected. Nuro has raised over $2B in capital from Uber, NVIDIA, Google, Softbank, Fidelity, T. Rowe Price, and other leading investors. About the Role Our software team is growing, and we are looking for talented engineers to join us and be instrumental to one of the following areas: Data Platform, Simulation, and Technical Infrastructure. Data Platform: The Data Platform serves as a comprehensive management system for Nuro AI Driver's data, labels, and metrics, facilitating seamless access functionality. The team focuses on data annotation across various domains, including 2D/3D perception, mapping, behavior trajectory, and language/text. It also handles data ingestion and mining, employing methods such as heuristics and embedding search. Additionally, the platform supports the autonomy evaluation infrastructure by providing detailed introspection. Simulation: The Simulation team builds the simulator that allows us to develop and test our autonomous driving technology in a virtual setting. We work on the core simulator and simulation frameworks, sensor simulation, scena

pythonci/cdmachine learning
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M
Mongodb
📍 Toronto• Full-time• From C$144K/yr
1mo ago

Platform Engineering is the department within SRE that is responsible for a range of critical infrastructure and operational functions that support the broader engineering organization. Among these are our multi-cloud-provider Kubernetes infrastructure, networking, load balancing (including our public-facing edge and internal service mesh), and observability and alerting systems. The Deployments team designs and maintains our continuous delivery infrastructure, ensuring reliable code deployment from development through production for all engineering teams. This infrastructure is primarily composed of Argo Workflows and ArgoCD. The team also provides tooling that enables clear system ownership and facilitates self-service onboarding for development teams. We are looking to speak to candidates who can work East Coast hours. The ideal candidate should Have 6+ years of experience in software development and operating distributed systems Proficiency in Python, Go, or a similar language Proven experience building and operating large-scale continuous integration and continuous deployment (CI/CD) pipelines Possess a customer-focused mindset Value efficiency in processes and operations Prefer automation over manual process (“allergic to ops work”). We are a small team of software engineers with a strong bias towards software solutions to avoid toil Experience using and extending containerization technologies, particularly Kubernetes, to enhance application agility, optimize resource utilization, and accelerate time-to-market Expertise in cloud infrastructure platforms, including AWS, Google Cloud Platform (GCP), or Azure Understanding of Linux operating system internals and networking concepts (e.g., TCP/IP, DNS, TLS, routing) Expectations Contribute to developing a world-class continuous deployment experience, enabling the rapid and reliable shipment of MongoDB products This includes, but is not limited to, contributing to open-source projects, or engineering software-based

pythonmongodbaws
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MongoDB’s Storage Layer Services (SLS) team is re-architecting the MongoDB cloud storage layer and sits at the heart of our next-generation cloud storage architecture. This relatively new team is building performant, multi-tenant distributed storage services that both enhance today’s Atlas storage stack and enable more customer workloads to run more efficiently. You will partner with the teams building these storage services to define SLOs, shape capacity plans, and ensure the reliability, durability, and operational safety of the storage layer that underpins Atlas. You’ll join a small, senior team of SREs as founding members of this organization, playing a crucial role in executing on a multi-year roadmap for MongoDB’s cloud storage architecture. This role can be based out of our Boston, New York City, Raleigh, Miami, Pittsburgh or remotely in the United States while physically based in an Eastern or Central time zone location. The ideal candidate should Have 6+ years of experience working on software development and operating distributed systems Proficiency in Python, Go, or a similar language Have operated or supported stateful storage or database systems at scale, and are comfortable with durability, consistency, and recovery trade-offs. Possess a customer-focused mindset Value efficiency in processes and operations Prefer automation over manual processes. We are a small team of software engineers with a strong bias towards software solutions to avoid toil Experience using and extending containerization technologies, particularly Kubernetes, to enhance application agility, optimize resource utilization, and accelerate time-to-market Expertise in cloud infrastructure platforms, including AWS, Google Cloud Platform (GCP), or Azure Understanding of Linux operating system internals and networking concepts (e.g., TCP/IP, DNS, TLS, routing) Responsibilities Work on our multi-tenant distributed storage systems, balancing long-term strategic infrastructure g

pythonmongodbaws
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M
1mo ago

Platform Engineering is the department within SRE that is responsible for a range of critical infrastructure and operational functions that support the broader engineering organization. Among these are our multi-cloud-provider Kubernetes infrastructure, networking, load balancing (including our public-facing edge and internal service mesh), and observability and alerting systems. The Deployments team designs and maintains our continuous delivery infrastructure, ensuring reliable code deployment from development through production for all engineering teams. This infrastructure is primarily composed of Argo Workflows and ArgoCD. The team also provides tooling that enables clear system ownership and facilitates self-service onboarding for development teams. We are looking to speak to candidates who can work East Coast hours. The ideal candidate should Have 6+ years of experience in software development and operating distributed systems Proficiency in Python, Go, or a similar language Proven experience building and operating large-scale continuous integration and continuous deployment (CI/CD) pipelines Possess a customer-focused mindset Value efficiency in processes and operations Prefer automation over manual process (“allergic to ops work”). We are a small team of software engineers with a strong bias towards software solutions to avoid toil Experience using and extending containerization technologies, particularly Kubernetes, to enhance application agility, optimize resource utilization, and accelerate time-to-market Expertise in cloud infrastructure platforms, including AWS, Google Cloud Platform (GCP), or Azure Understanding of Linux operating system internals and networking concepts (e.g., TCP/IP, DNS, TLS, routing) Expectations Contribute to developing a world-class continuous deployment experience, enabling the rapid and reliable shipment of MongoDB products This includes, but is not limited to, contributing to open-source projects, or engineering software-based

pythonmongodbaws
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The Team MongoDB’s Storage Layer Services (SLS) team is re-architecting the MongoDB cloud storage layer and sits at the heart of our next-generation cloud storage architecture. This relatively new team is building performant, multi-tenant distributed storage services that both enhance today’s Atlas storage stack and enable more customer workloads to run more efficiently. You will partner with the teams building these storage services to define SLOs, shape capacity plans, and ensure the reliability, durability, and operational safety of the storage layer that underpins Atlas. You’ll join a small, senior team of SREs as founding members of this organization, playing a crucial role in executing on a multi-year roadmap for MongoDB’s cloud storage architecture. This role can be based out of either our Dublin or Cork office or remotely in Ireland. The ideal candidate should Have 6+ years of experience working on software development and operating distributed systems Proficiency in Python, Go, or a similar language Have operated or supported stateful storage or database systems at scale, and are comfortable with durability, consistency, and recovery trade-offs. Possess a customer-focused mindset Value efficiency in processes and operations Prefer automation over manual processes. We are a small team of software engineers with a strong bias towards software solutions to avoid toil Experience using and extending containerization technologies, particularly Kubernetes, to enhance application agility, optimize resource utilization, and accelerate time-to-market Expertise in cloud infrastructure platforms, including AWS, Google Cloud Platform (GCP), or Azure Understanding of Linux operating system internals and networking concepts (e.g., TCP/IP, DNS, TLS, routing) Responsibilities Work on our multi-tenant distributed storage systems, balancing long-term strategic infrastructure goals with immediate engineering needs Build for reliability, making services and infrastructure avail

pythonmongodbaws
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We are looking for an experienced Senior or Staff Engineer for our SRE, InfraSec team, to guide the security of our cloud-based infrastructure. As a Staff SRE, you will be very hands-on technically while also mentoring a small team of SREs. The InfraSec team collaborates closely with other engineering teams to ensure that our infrastructure adheres to the highest security standards. They build essential security infrastructure and implement controls that reinforce the platform’s security posture. This is an SRE team, which means you can expect a highly hands-on approach, tackling the technical challenges of implementing large scale solutions.This team is deeply involved in the technical aspects of security and the nuances of its actual implementation. This role can sit in our New York City, Austin, Seattle or San Francisco offices on a hybrid basis, or it can be fully remote while working from a location based in either Eastern or Central time zones. Responsibilities: Cloud Security Design and Implementation: Help lead the design and deployment of security solutions for cloud platforms (AWS, Azure, GCP), including network and compute security, identity management, and cloud security posture management (CSPM) Automation and Monitoring: Build automated solutions for real-time security monitoring, logging, and alerting in cloud environments. Leverage native cloud services and third-party tools for runtime security monitoring and anomaly detection Security Tooling: Evaluate, implement, and manage cloud-native security tools and platforms for endpoint security, identity management (IAM), and CSPM Qualifications: Experience: 6+ years of experience in SRE, infrastructure engineering or similar role, with a strong focus on security work, with ideally 2+ years in a senior or staff engineering role Security Mindset: A comprehensive understanding of all facets of cloud environment security, spanning from foundational OS networking laye

mongodbawsazure
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MongoDB’s Storage Layer Services (SLS) team is re-architecting the MongoDB cloud storage layer and sits at the heart of our next-generation cloud storage architecture. This relatively new team is building performant, multi-tenant distributed storage services that both enhance today’s Atlas storage stack and enable more customer workloads to run more efficiently. You will partner with the teams building these storage services to define SLOs, shape capacity plans, and ensure the reliability, durability, and operational safety of the storage layer that underpins Atlas. You’ll join a small, senior team of SREs as founding members of this organization, playing a crucial role in executing on a multi-year roadmap for MongoDB’s cloud storage architecture. This role can be based out of our Toronto or Montreal office or remotely in the Canada while physically based in an Eastern or Central time zone location. The ideal candidate should Have 6+ years of experience working on software development and operating distributed systems Proficiency in Python, Go, or a similar language Have operated or supported stateful storage or database systems at scale, and are comfortable with durability, consistency, and recovery trade-offs. Possess a customer-focused mindset Value efficiency in processes and operations Prefer automation over manual processes. We are a small team of software engineers with a strong bias towards software solutions to avoid toil Experience using and extending containerization technologies, particularly Kubernetes, to enhance application agility, optimize resource utilization, and accelerate time-to-market Expertise in cloud infrastructure platforms, including AWS, Google Cloud Platform (GCP), or Azure Understanding of Linux operating system internals and networking concepts (e.g., TCP/IP, DNS, TLS, routing) Responsibilities Work on our multi-tenant distributed storage systems, balancing long-term strategic infrastructure goals with immediate engineerin

pythonmongodbaws
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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. Senior Software Engineer — Cortex Training The Snowflake ML Platform team's mission is to let customers run their most demanding ML/AI workloads inside Snowflake. Cortex Training is our LLM post-training platform: it turns scarce, expensive GPU capacity into a simple, composable service, so customers can adapt open-weight foundation models to their own business problems while we handle the hard distributed-systems parts, including scheduling, orchestration, multi-node training and inference, fault tolerance, and throughput. The platform already runs post-training at scale. Under the hood, it decouples GPU computation from the training loop and exposes it as primitive APIs that compose into everything from SFT to full RL workflows. You'll work alongside a team that ships fast & sweats reliability and the researchers behind DeepSpeed. We're looking for an engineer who thrives in the ML infrastructure layer and brings a solid understanding of LLMs and post-training to help us scale and grow it. YOU WILL: Design and build across the full stack — from the public training APIs and SDK through the control plane to the GPU data plane. Scale the distributed systems that make GPU compute serverless — multi-tenant scheduling, placement, and capacity-aware routing across regional G

kubernetesaigo
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