Infrastructure Support Engineer Jobs

Location: South Jordan, UT (This role is on-site) Salary: $56,000 - $58,000 USD Want to work in technology at an investment bank? Graduate training, ongoing support, opportunities at leading global employers – the Alumni graduate program gives you everything you need. (And don’t worry, there’s no training bond. No exit fees, no hidden catches). Here at mthree, we pair great graduates with brilliant global businesses. Our clients include tier one investment banks and other organizations across a range of industries, from insurance to healthcare to travel. As part of the mthree Alumni program, mthree has an exciting and exclusive partnership with Columbia Univ. School of Engineering. All mthree Alumni are eligible to receive two Executive Education certificates from Columbia Engineering as part of their Academy and industry placement experience at no cost. Further, all participating Alumni will have access to the Columbia Engineering network and ongoing training. What you'll do: Production support plays a vital role in enterprise technology, from algorithmic trading engines to regulatory reporting. Think of it as healthcare for technology. As a production support analyst with mthree, you’ll be on a shared mission to look after the technical systems and processes other teams rely on. How the Alumni program works: Apply via this job advert. Complete our assessment process. Get trained at mthree Academy in an online class for 4-8 weeks with other graduates. Join a mthree client for 12-24 months while receiving support and salary increases every 12 months. The vast majority then convert to permanent employees with the client at the end of the program. What you’ll learn at the mthree Academy: How to discuss production support activity at a high level including ITIL (information technology infrastructure library), monitoring, DevOps, SRE (site reliability engineering), and disaster recovery. How to discuss common financial topics, including financial markets, e

Locations: United States - we are looking for candidates who are flexible to working onsite in multiple locations across the United States. Salary: $48,000 - $63,000 USD Want to work in technology at an investment bank? Graduate training, ongoing support, opportunities at leading global employers – the Alumni graduate program gives you everything you need. (And don’t worry, there’s no training bond. No exit fees, no hidden catches). Here at mthree, we pair great graduates with brilliant global businesses. Our clients include tier one investment banks and other organizations across a range of industries, from insurance to healthcare to travel. What you'll do: Production support plays a vital role in enterprise technology, from algorithmic trading engines to regulatory reporting. Think of it as healthcare for technology. As a production support analyst with mthree, you’ll be on a shared mission to look after the technical systems and processes other teams rely on. How the Alumni program works: Apply via this job advert. Complete our assessment process. Get trained at mthree Academy in an online class for 4-8 weeks with other graduates. Join a mthree client for 12-24 months while receiving support and salary increases every 12 months. The vast majority then convert to permanent employees with the client at the end of the program. What you’ll learn at the mthree Academy: How to discuss production support activity at a high level including ITIL (information technology infrastructure library), monitoring, DevOps, SRE (site reliability engineering), and disaster recovery. How to discuss common financial topics, including financial markets, equity trading, derivatives, currency, treasury, regulation, and risk. How to write a basic computer program in Python, including user input, common data structures, and flow of control. How to use MySQL to perform CRUD (create, read, update and delete) operations on a relational database stored in a MySQL Server. What

P-78 While candidates in the listed locations are encouraged for this role, candidates in other locations will be considered. 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 solve 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 Infrastructure teams, you will build scalable systems to power the Databricks platform, making it the de-facto platform for running Big Data and AI workloads. You will build and extend the Databricks infrastructure platform, which includes multi-cloud systems and services for managing thousands of Kubernetes clusters at scale, storing petabytes of data, highly scalable and distributed API gateways, rate limiting framework, network security and encryption, developer tools and infrastructure (we use Bazel), testing frameworks, and scalable CI/CD framework among many others. The impact you will have: Build and extend components of the core Databricks infrastructure Architect multi-cloud systems and abstractions to allow the Databricks product to run on top of existing Cloud providers Improve software development workflows for engineering and operational efficiency. Use our own data and AI platform (yes!) to analyze build and test logs and metrics to identify areas for improvement. Develop automated build, test, and release infrastructures. Set and uphold the standard for engineering processes to support high-quality engineering, including style and code checking, test harness

Job Title: DevOps Engineer/ Production Support Analyst Location: Salt Lake City, UT Salary: $45,000 - $54,000 USD/year Want to work in technology at an investment bank? In-depth graduate training, ongoing support, opportunities at leading global employers – the Alumni graduate program gives you everything you need. (And don’t worry, there’s no training bond. No exit fees, no hidden catches). Here at mthree, we pair great graduates with brilliant global businesses. Our clients include tier one investment banks and other organizations across a range of industries, from insurance to healthcare to travel. As part of the mthree Alumni program, mthree has an exciting and exclusive partnership with Columbia Univ. School of Engineering. All mthree Alumni are eligible to receive two Executive Education certificates from Columbia Engineering as part of their Academy and industry placement experience at no cost. Further, all participating Alumni will have access to the Columbia Engineering network and ongoing training. What you'll do: Production support plays a vital role in enterprise technology, from algorithmic trading engines to regulatory reporting. Think of it as healthcare for technology. As a production support analyst with mthree, you’ll be on a shared mission to look after the technical systems and processes other teams rely on. How the Alumni program works: Apply via this job advert. Complete our assessment process. Get trained at mthree Academy in an online class for 4-8 weeks with other graduates. Join a mthree client for 12-24 months while receiving support and salary increases every 9 months. The vast majority then convert to permanent employees with the client at the end of the program. What you’ll learn at the mthree Academy: How to discuss production support activity at a high level including ITIL (information technology infrastructure library), monitoring, DevOps, SRE (site reliability engineering), and disaster recovery. How to d

About the Team Data Platform at OpenAI owns the foundational data stack powering critical product, research, and analytics workflows. We operate some of the largest Spark compute fleets in production; design, and build data lakes and metadata systems on Iceberg and Delta with a vision toward exabyte-scale architecture; run high throughput streaming platforms on Kafka and Flink; provide orchestration with Airflow; and support ML feature engineering tooling such as Chronon. Our mission is to deliver reliable, secure, and efficient data access at scale and accelerate intelligent, AI assisted data workflows. Join us to build and operate these core platforms that underpin OpenAI products, research, and analytics. We’re not just scaling infrastructure – we’re redefining how people interact with data. Our vision includes intelligent interfaces and AI-assisted workflows that make working with data faster, more reliable, and more intuitive. About the Role This role focuses on building and operating data infrastructure that supports massive compute fleets and storage systems, designed for high performance and scalability. You’ll help design, build, and operate the next generation of data infrastructure at OpenAI. You will scale and harden big data compute and storage platforms, build and support high-throughput streaming systems, build and operate low latency data ingestions, enable secure and governed data access for ML and analytics, and design for reliability and performance at extreme scale. You will take full lifecycle ownership: architecture, implementation, production operations, and on-call participation. You’ve supported Spark, Kafka, Flink, Airflow, Trino, or Iceberg as platforms. You’re well-versed in infrastructure tooling like Terraform, experienced in debugging large-scale distributed systems, and excited about solving data infrastructure problems in the AI space. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per wee

Who we are About Stripe Stripe is a financial infrastructure platform for businesses. Millions of companies, from the world's largest enterprises to the most ambitious startups, use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone's reach while doing the most important work of your career. About the team Stripe's Infrastructure organization builds and operates the shared platforms that make it possible for engineering teams to build, deploy, run, and scale reliable products. The organization owns foundational capabilities across service networking and discovery, safe feature and configuration changes, data storage and orchestration, and batch computing. Our platforms support a global engineering audience and power systems at significant scale. This includes the control plane for secure service-to-service communication across tens of thousands of microservices, service and feature deployment infrastructure that helps teams introduce and recover from changes safely, infrastructure for running Stripe's containerized services, and data platforms for storage, pipeline orchestration, and large-scale processing. Our batch compute platforms support technologies including Apache Airflow, Apache Spark, Apache Iceberg, Apache Hadoop, and Apache Celeborn. As an Engineering Manager, you will lead or strongly influence teams working on business-critical infrastructure with broad internal adoption. You will balance reliability, scalability, security, developer experience, and operational rigor while helping Stripe move quickly with confidence. You will partner closely with product, security, data, support, and adjacent infrastructure leaders to set direction, resolve cross-team dependencies, and turn recurring needs into durable platform capabilities. Wh

Why Sony Interactive Entertainment? Sony Interactive Entertainment isn’t just the Best Place to Play — it’s also the Best Place to Work. Sony Interactive Entertainment (SIE) is the company behind the PlayStation brand. As a subsidiary of Sony Group Corporation, we’re part of a proud legacy of innovation and excellence. SIE is a dynamic technology company, delivering cutting-edge hardware and network services to more than 100 million people and an entertainment leader, home to some of the most beloved and recognizable intellectual properties (IP) in the world. Our role at SIE is to create and nurture the experiences under the PlayStation brand, a name synonymous with entertainment excellence and creativity. Technical Operations Support (TOS) Analyst HYBRID: Aliso Viejo, CA Contract, 12 months As part of Sony Interactive Entertainment, GDFT is helping lead the cloud gaming revolution, delivering console-quality gaming experiences across televisions, consoles, mobile devices, and beyond. The Technical Operations Support (TOS) team is a critical component of the operational foundation that enables GDFT to support a global cloud gaming platform at scale. The team provides frontline operational support for infrastructure, services, and internal processes that help ensure reliable delivery of world-class streaming experiences to players around the world. As a Technical Operations Support Analyst, you will serve as a key operational partner responsible for handling support requests, maintaining operational processes, documenting procedures, and helping improve the efficiency of day-to-day operations. You will work closely with technical operations, engineering, and global support teams while developing foundational skills in cloud and datacenter infrastructure, operational support, troubleshooting, and process improvement. Key Responsibilities: Operational Support Acknowledge, triage, and resolve support requests by following established Standard Operating Procedures

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Lovable , Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September. Our team includes creators of popular open-source projects (e.g., Seaborn , Luig i ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. The Role: We're looking for Forward Deployed ML Engineers who want to work at the intersection of deep technical work and direct customer impact. As an ML FDE, you'll partner with leading AI companies and foundation model labs to help them achieve state-of-the-art performance on their most demanding workloads — LLM serving, model training (SFT, RLHF), audio pipelines, scientific computing, and more. You're helping teams reach outcomes most engineers can't on their own. The FDE team today includes world-class software engineers, computational scientists, ML engineers, and former founders. We're looking for people with strong engineering fundamentals, deep curiosity across the AI stack, and energy for working directly with customers on hard problems. You will: Work hands-on with companies like Suno, Lovable, Cognition, and Meta to architect and optimize production AI workloads

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We've passed $1B in annualized run rate, up 15x from a year ago. In October 2026 we raised a $750M Series D led by Accel at a $15.75B valuation. Our team includes creators of popular open-source projects (e.g., Seaborn , Luigi ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. The Role: We're looking for Forward Deployed ML Engineers who want to work at the intersection of deep technical work and direct customer impact. As an ML FDE, you'll partner with leading AI companies and foundation model labs to help them achieve state-of-the-art performance on their most demanding workloads — LLM serving, model training (SFT, RLHF), audio pipelines, scientific computing, and more. You're helping teams reach outcomes most engineers can't on their own. The FDE team today includes world-class software engineers, computational scientists, ML engineers, and former founders. We're looking for people with strong engineering fundamentals, deep curiosity across the AI stack, and energy for working directly with customers on hard problems. You will: Work hands-on with companies like Suno, Lovable, Cognition, and Meta to architect and optimize production AI workloads on Modal Contribute to open-sour

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Lovable , Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September. Our team includes creators of popular open-source projects (e.g., Seaborn , Luig i ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. The Role: Modal is seeking an experienced Forward Deployed Engineer (FDE) to partner with our sales team and drive technical sales success. As an FDE, you will be the technical voice in our sales process, working directly with Account Executives to help enterprise customers understand how Modal can transform their AI/ML infrastructure. You will: Partner with Account Executives to identify, qualify, and close strategic enterprise opportunities Lead technical discovery sessions with prospective customers to understand their current infrastructure, pain points, and requirements Design and present compelling technical solutions that demonstrate how Modal addresses customer needs Architect migration paths from existing cloud infrastructure (AWS, GCP, Azure) to Modal's serverless platform Conduct technical demos, experiments, and proof-of-concepts that showcase Modal's capabilitie

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We've passed $1B in annualized run rate, up 15x from a year ago. In October 2026 we raised a $750M Series D led by Accel at a $15.75B valuation. Our team includes creators of popular open-source projects (e.g., Seaborn , Luigi ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. The Role: We're looking for Forward Deployed Engineers on our engineering team who want to work at the intersection of deep infrastructure work and direct customer impact. As an FDE, you'll partner with leading AI companies and foundation labs on cloud architecture, networking, storage, containerization, sandboxing, and more — helping them design and ship production infrastructure on Modal's platform. The FDE team today includes world-class software engineers, computational scientists, ML engineers, and former founders. We're looking for people with strong engineering fundamentals, deep curiosity across the infrastructure stack, and energy for working directly with customers on hard problems. You will: Work hands-on with companies like Suno, Lovable, Cognition, and Meta to architect and deploy massive-scale production workloads on Modal Lead technical discovery and architecture sessions with prospective and

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We've passed $1B in annualized run rate, up 15x from a year ago. In October 2026 we raised a $750M Series D led by Accel at a $15.75B valuation. Our team includes creators of popular open-source projects (e.g., Seaborn , Luigi ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. The Role: Modal builds AI infrastructure products that developers love. That's how we grew so quickly, and why word of mouth remains one of our most important channels today. In this role, you will primarily create and distribute technical content that is unique, educational, and practical. This content will be the first Modal touchpoint for many of our users. We want to not only showcase the power and developer experience of Modal, but also serve as a trusted resource for them when implementing new AI technologies. In this role, you will: Distill the latest advancements in AI technology and educate developers on how to incorporate them. Give demos/talks about Modal and adjacent tools at developer events. Engage with users in our community, both online (X, LinkedInReddit, Slack) and at in-person events. Build relationships, integrations, and joint marketing activities with other developer-focused companies

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Lovable , Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September. Our team includes creators of popular open-source projects (e.g., Seaborn , Luig i ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. The Role: Modal builds AI infrastructure products that developers love. That's how we grew so quickly and why word-of-mouth remains one of our most important channels today. From powering one of the largest vibe-coding platforms at Lovable to enabling teams like Ramp to build their own internal coding agents , Modal Sandboxes are used by developers to safely execute AI-generated code at scale. We're now hiring our first developer relations engineer focused on Modal Sandboxes. Whether it’s banger tweets , in-depth technical resources or long-form talks , we want to meet developers by any medium necessary and empower them to build and ship novel AI products. In this role, you will primarily be creating and distributing technical content that is unique, educational, and practical. This content will be the first Modal touchpoint for many of our users. We want to not only showcas

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We've passed $1B in annualized run rate, up 15x from a year ago. In October 2026 we raised a $750M Series D led by Accel at a $15.75B valuation. Our team includes creators of popular open-source projects (e.g., Seaborn , Luigi ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. About GTM Engineering: GTM Engineering is responsible for the data, business logic, workflows, and agents that enable our Marketing and Sales teams to help customers get the most out of Modal. Like the infrastructure beneath the Magic Kingdom , much of our work happens behind the scenes. We build systems that anticipate and deliver what customers need to grow on Modal. We bring a product management, growth engineering, and data science approach to GTM, from centralizing our data platform to building agents for account research . We're looking for a GTM Engineer to own our GTM data platform. This role combines analytics engineering with revenue operations: you'll build the org map, people graph, and data systems that help us discover future customers and support our GTM workflows, partnering closely with our Data team on the shared foundation. What You'll Do: Build and maintain an org map and people graph co

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We've passed $1B in annualized run rate, up 15x from a year ago. In October 2026 we raised a $750M Series D led by Accel at a $15.75B valuation. Our team includes creators of popular open-source projects (e.g., Seaborn , Luigi ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. About the Data Team: We’re growing our Data team and are looking for our first few key hires to build self-serve data tools and drive business strategy in the right direction. The mission of the Modal Data team is to make it easy to track company goals, make evidence-backed decisions, and prioritize the right work. We do this via: Self-serve AI analytics tools (Hex, Snowflake) Embedding with teams as a “data adviser”, providing strategic analysis and consulting What You'll Do: Contribute to building the most modern analytics stack in Data today to support AI-driven self-serve analysis, key metrics tracking, and external customer reporting Influence work on new products like LLM Inference Endpoints through product analytics tracking Identify millions of dollars of cost savings and optimization across our tools and financial operations Write data pipelines that power the operations of our business, such as ou