Cloud Operations Engineer Jobs

SDLC Engineer A Career with Point72’s Technology Team As Point72 reimagines the future of investing, our Technology group is constantly improving our company’s IT infrastructure, positioning us at the forefront of a rapidly evolving technology landscape. We’re a team of experts experimenting, discovering new ways to harness the power of open-source solutions, and embracing enterprise agile methodology. We encourage professional development to ensure you bring innovative ideas to our products while satisfying your own intellectual curiosity. What You’ll Do Provide expert technical support for our enterprise Software Development Life Cycle (SDLC) platforms including Jenkins, GitHub, Bitbucket, and AWS-based CI/CD pipelines Support and optimize our artifact management solutions (Artifactory) and static code analysis tools (SonarQube) Partner directly with business teams and development clients to address SDLC platform challenges and deliver effective solutions Implement and maintain security controls across our development toolchain and infrastructure Develop automation solutions to eliminate toil and enhance developer productivity Troubleshoot complex build, deployment, and integration issues across our development environments Contribute to continuous improvement of our AWS-based development infrastructure Maintain documentation and knowledge base for supported platforms and tools What’s required 5+ years of experience in software engineering, DevOps, or SRE roles Strong technical expertise in AWS services and cloud-native architectures Experience with container technologies (Docker, ECS, EKS) and container orchestration Deep understanding of Git workflows, branching strategies, and version control best practices Strong hands-on programming/scripting skills (Python, Go, or similar), with ability to debug and build automation for CI/CD pipelines Experience with infrastructure as code (Terraform, CloudFormation) in AWS environments Hands-on experience with CICD solutio

Help shape the technology that enables a global organisation to do its best work. As Senior Manager, Platform Engineering, you’ll lead the team responsible for Diligent’s Atlassian and Microsoft platforms while setting the architectural direction for the wider internal IT estate. You’ll combine people leadership, enterprise platform strategy and hands-on technical judgement to create secure, reliable and scalable experiences for employees worldwide. From modernising service management and automating joiner, mover and leaver processes to enabling AI safely through Microsoft Copilot and Atlassian Rovo, your work will reduce friction, strengthen governance and deliver measurable business impact. Working across IT, Security, HR, Finance, Legal, Compliance and business teams, you’ll turn complex requirements into well-governed platforms that are easy to use, resilient and ready for the future. Here’s a breakdown of what you’ll do (not all of it, just the important stuff) Lead, coach and grow a global team of platform engineers and systems administrators, building a high-performing and inclusive culture. Own the strategy, architecture, governance and roadmap for Atlassian Cloud, including Jira, Jira Service Management, Confluence, Atlassian Guard and Rovo. Set the direction for Diligent’s Microsoft 365 E5 estate, including Teams, SharePoint, Exchange Online, Intune, Defender, Purview, Power Platform and Copilot. Design scalable integration and automation patterns across identity, HRIS, ITSM and business systems using APIs, event-driven automation, Okta Workflows, Power Platform and scripting. Partner with IT Support to improve self-service, automate repetitive work and reduce ticket volume, escalation effort and time to resolution. Establish strong standards for security, access governance, AI adoption, reliability, compliance and business continuity across the internal technology estate. These are the essentials you’ll need to get an interview Significant experience in i

Position Overview: As a Software Engineer II at Diligent, you’ll take on a hands-on technical role in building secure, scalable, and high-performing serverless microservices using TypeScript on AWS. You’ll contribute meaningfully to our mission of making governance effortless for our customers, working in a team of passionate and talented individuals that owns its services end to end—from architecture and implementation to monitoring and continuous improvements. This role is ideal for a mid-level engineer who writes solid code and embraces AI-powered tools to work smarter and faster. You’ll help shape architectural discussions, and scale modern development practices, including responsible use of AI in workflows. Key Responsibilities Design and implement secure, scalable, high-performing, yet simple solutions using AWS Serverless technology. These solutions should strive to be event-driven, highly observable, with infrastructure as code, and tightly leveraging AWS’s ecosystem of services. Optimize your development and delivery experience in order to maximize your team’s productivity and deploy continuously to production. Work in a collaborative environment where you regularly pair, plan, and execute tasks as a team and maintain a healthy development flow by adhering to Agile processes and driving iterative enhancements. Use AI tools to accelerate coding, debugging, testing, research, and code reviews, always validating outputs and applying judgment. Required Experience/Skills 3–5 years of professional software engineering experience in an agile, fast-paced environment. AI Tooling & Practices: Uses AI to boost productivity, skilled in prompt engineering, and evaluates AI outputs responsibly (bias, cost, ethics). Familiar with core AI concepts (tokens, context length, embeddings, hallucinations), understands high-level LLM behavior, and recognizes safe vs. unsafe use cases (privacy, security, fairness). Cloud & infrastructure basics: Hands-on with AWS ser

Here’s a summary of the role: Lead a strong engineering team, deliver software that matters, and help people do the best work of their careers. This is a hands-on team management role for someone who enjoys combining people leadership, technical fluency, and modern AI-enabled ways of working to build reliable products at scale. You’ll lead engineers building secure, scalable microservices and APIs using TypeScript and AWS. You’ll partner closely with Product, Security, DevOps, and peer engineering leaders to deliver roadmap outcomes, improve team effectiveness, and create an environment where engineers can grow, own their work, and build high-quality systems with confidence. Here’s a breakdown of what you’ll do, not all of it, just the important stuff: Lead, coach, and support a team of engineers, creating clarity around priorities, ownership, expectations, and growth goals. Partner with Product, Security, DevOps, and peer engineering leaders to plan and deliver roadmap commitments while balancing quality, pace, and sustainability. Create a healthy delivery environment by improving team processes, removing blockers, supporting planning and estimation, and reinforcing strong engineering practices. Maintain enough technical depth to guide design discussions, challenge risks, review trade-offs, and support the team in building secure and maintainable systems. Use AI tools and encourage responsible AI-assisted ways of working that improve productivity while protecting privacy, security, quality, and good judgment. Support hiring, feedback, performance conversations, and career development so the team continues to grow in capability and confidence. These are the essentials you’ll need to get an interview: 8 or more years of software engineering experience, including experience leading projects and supporting or managing engineers in an agile product environment. Experience managing teams that build cloud-native microservices in AWS. Strong people leadership skills, with

Most security assurance work is reactive: a customer asks, a team scrambles, an answer goes out. This role exists to end that cycle. As a Senior Staff Analyst, you’ll own a named portfolio of our most significant customers from a security perspective, and get ahead of what they need — their regulatory environment, their audit calendar, their risk appetite, their control expectations — well enough to have the evidence ready before the request arrives. You’ll lead customer security audits hands-on, sit across from customer security teams as a peer rather than a form-filler, and build account security plans that make the next assessment predictable instead of painful. This is deliberately a hands-on senior individual contributor role. You’ll spend your time in audits, in customer conversations, and in the detail of controls and evidence — not in a management chain. If you’ve got deep SOC 2 and ISO 27001 knowledge, real technical range across cloud architecture, identity and vulnerability management, and the presence to hold a room with a sceptical CISO, this is a portfolio you can genuinely own. Here’s a breakdown of what you’ll do (not all of it, just the important stuff): Own a portfolio of strategic accounts as their dedicated security point of contact, building durable relationships with their security, risk, compliance and procurement teams. Lead customer security audits and assessments hands-on — scoping, preparing evidence, running the sessions, defending control design and driving findings to closure with internal owners. Build and maintain an account security plan for each account: their frameworks and regulators, audit and reassessment cycles, known concerns, open items and the roadmap commitments they care about. Anticipate requirements before they’re raised, tracking regulatory change, industry expectations and each account’s compliance calendar so documentation and evidence are staged in advance. Act

The Public Sector software engineers (SWEs) create the core product building blocks forward-deployed teams use to develop agentic capabilities that function across multiple domains. SWEs responsibilities include building the systems required to ingest and process federal datasets to support real-time decision-making in contested environments. We develop novel agentic enabling capabilities that includes: Create multi-layered guardrails around agents Optimize data retrieval for agents Orchestrate fleets of asynchronous agents Automatically alerts users to deviations in data Illustrating how an agent reached a decision As a Staff Software Engineer, you will orchestrate the implementation of vertical features and horizontal capabilities to include mentoring other engineers on defining requirements with stakeholders and communication tradeoffs of technical implementations on feature and capabilities until they are accepted by the stakeholders. You will: Orchestrate feature implementation across the Federal engineering team to ensure architectural consistency. Define technical strategy for agentic guardrails, explainability, and fleet orchestration. Ensure system reliability and performance across multiple security classifications and network types. Mentor engineers in the process of defining requirements with stakeholders and gathering acceptance. Communicate high-level technical trade-offs and implementation strategies to senior government stakeholders and Scale C-Suite members. Influence the long-term product strategy and technical roadmap for the Federal business unit. Consult on the architecture of AI-powered solutions for large-scale federal contracts. Ideally you will have: Full Stack Development: Proficiency in front-end, back-end development and infrastructure, including experience with modern web development frameworks, programming languages, and databases Cloud-Native Technologies: Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and experience in

Scale GP (Scale Generative AI Platform) is an enterprise-grade Generative AI platform that provides APIs for knowledge retrieval, inference, evaluation, and more. We are looking for a strong engineer to join our team and help us build and scale our product in a fast-paced environment. The ideal candidate will have a strong understanding of software engineering principles and practices, as well as experience with large-scale distributed systems. You will be responsible for owning large new areas within our product, working across backend, frontend, and interacting with LLMs and ML models. You will solve hard engineering problems in scalability and reliability. You will: Own large new areas within our product Work across backend, frontend, and interacting with LLMs and ML models Deliver experiments at a high velocity and level of quality to engage our customers Work across the entire product lifecycle from conceptualization through production Be able, and willing, to multi-task and learn new technologies quickly Ideally you'd have: 7+ years of full-time engineering experience, post-graduation Experience scaling products at hyper growth startups Experience tinkering with or productizing LLMs, vector databases, and the other latest AI technologies Proficient in Python or Javascript/Typescript, and SQL Experience with Kubernetes Experience with major cloud providers (AWS, Azure, GCP) Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position and may be inclusive of several career levels at Scale; it will be determined during the interview process based on work location and additional factors, including job-related skills, experience, qualifications, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval

About Scale AI Scale AI is the data foundation for AI, helping organizations build and deploy reliable production AI applications. We partner with leading enterprises and government organizations to accelerate their AI initiatives through our data annotation platform, generative AI solutions, and enterprise AI capabilities. Role Overview As a Forward Deployed AI Engineering Manager on our Enterprise team, you'll be the technical bridge between Scale AI's cutting-edge AI capabilities and our most strategic customers. You'll work with enterprise clients to understand their unique challenges, lead a team that architects specific AI solutions, and ensure successful deployment and adoption of AI systems in production environments. This is a Management role that combines deep engineering and AI expertise, leading a team, and working on customer-facing problems. You'll work directly with customer engineering teams to integrate AI into their critical workflows. Key Responsibilities Customer Integration & Deployment Partner directly with enterprise customers to understand their technical infrastructure, data pipelines, and business requirements Design and implement custom integrations between Scale AI's platform and customer data environments (cloud platforms, data warehouses, internal APIs) Build robust data connectors and ETL pipelines to ingest, process, and prepare customer data for AI workflows Deploy and configure AI models and agents within customer security and compliance boundaries AI Agent Development Develop production-grade AI agents tailored to customer use cases across domains like customer support, data analysis, content generation, and workflow automation Architect multi-agent systems that orchestrate between different models, tools, and data sources Implement evaluation frameworks to measure agent performance and iterate toward business objectives Design human-in-the-loop workflows and feedback mechanisms for continuous agent improvement Prompt Engineeri

About Scale AI Scale AI is the data foundation for AI, helping organizations build and deploy reliable production AI applications. We partner with leading enterprises and government organizations to accelerate their AI initiatives through our data annotation platform, generative AI solutions, and enterprise AI capabilities. Role Overview As a Senior Staff Frontier Agents Engineer on our Enterprise team, you'll be the technical bridge between Scale AI's cutting-edge AI capabilities and our most strategic customers. You'll work with enterprise clients to understand their unique challenges, architect custom AI solutions, and ensure successful deployment and adoption of AI systems in production environments. This is a hands-on technical role that combines deep engineering expertise with customer-facing problem solving. You'll work directly with customer engineering teams to integrate AI into their critical workflows. Key Responsibilities Customer Integration & Deployment Partner directly with enterprise customers to understand their technical infrastructure, data pipelines, and business requirements Design and implement custom integrations between Scale AI's platform and customer data environments (cloud platforms, data warehouses, internal APIs) Build robust data connectors and ETL pipelines to ingest, process, and prepare customer data for AI workflows Deploy and configure AI models and agents within customer security and compliance boundaries AI Agent Development Develop production-grade AI agents tailored to customer use cases across domains like customer support, data analysis, content generation, and workflow automation Architect multi-agent systems that orchestrate between different models, tools, and data sources Implement evaluation frameworks to measure agent performance and iterate toward business objectives Design human-in-the-loop workflows and feedback mechanisms for continuous agent improvement Prompt Engineering & Optimization Create sophisticate

The Public Sector software engineers (SWEs) create the core product building blocks forward-deployed teams use to develop agentic capabilities that function across multiple domains. SWEs responsibilities include building the systems required to ingest and process federal datasets to support real-time decision-making in contested environments. We develop novel agentic enabling capabilities that includes: Create multi-layered guardrails around agents Optimize data retrieval for agents Orchestrate fleets of asynchronous agents Automatically alerts users to deviations in data Illustrating how an agent reached a decision As a Senior Software Engineer, you will lead the development of a vertical feature or a horizontal capability to include defining requirements with stakeholders and implementation until it is accepted by the stakeholders. You will: Lead the design and implementation of scalable backend systems and distributed architectures for Federal customers. Manage the full lifecycle of feature development from requirement definition to deployment on classified networks. Direct the orchestration of asynchronous agent fleets to meet mission requirements. Lead customer engagements to translate mission needs into technical requirements. Own the communication with stakeholders to ensure implementation meets defined acceptance criteria. Conduct technical reviews and identify risks within machine learning infrastructure and model serving. Drive the platform roadmap by providing technical specifications for Federal product offerings. Ideally you will have: Full Stack Development: Proficiency in front-end, back-end development and infrastructure, including experience with modern web development frameworks, programming languages, and databases Cloud-Native Technologies: Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and experience in developing and deploying applications in a cloud-native environment. Understanding of containerization (e.g., Docker) and contai

Software is eating the world, but AI is eating software. We live in unprecedented times – AI has the potential to exponentially augment human intelligence. Every person will have a personal tutor, coach, assistant, personal shopper, travel guide, and therapist throughout life. As the world adjusts to this new reality, leading platform companies are scrambling to build LLMs at billion scale, while large enterprises figure out how to add it to their products. To make them safe, aligned and actually useful, these models need human eval and reinforcement learning through human feedback (RLHF) during pre-training, fine-tuning, and production evaluations. This is the main innovation that’s enabled ChatGPT to get such a large headstart among competition. At Scale, our products include the Generative AI Data Engine, SGP, Donovan, and others that power the most advanced LLMs and generative models in the world through world-class RLHF, human data generation, model evaluation, safety, and alignment. The data we are producing is some of the most important work for how humanity will interact with AI. At the foundation of these products is the Platform Engineering team. In this role, you will support the design and development of shared platforms used across Scale. This includes designing our foundational data platforms and lifecycle, architecting Scale’s core cloud infrastructure and orchestration stack, and redefining how engineers develop, build, test, and deploy software at Scale. You’ll also get widespread exposure to the forefront of the AI race as Scale sees it in enterprises, startups, governments, and large tech companies. You will: Drive the design, and implementation of our foundational platforms and systems, working closely with stakeholders and internal customers to understand and refine requirements. Collaborating with cross-functional teams to define, design, and deliver new features. Proactively identifying opportunities for, and driving improvements to, current p

Software is eating the world, but AI is eating software. We live in unprecedented times – AI has the potential to exponentially augment human intelligence. Every person will have a personal tutor, coach, assistant, personal shopper, travel guide, and therapist throughout life. As the world adjusts to this new reality, leading platform companies are scrambling to build LLMs at billion scale, while large enterprises figure out how to add it to their products. To make them safe, aligned and actually useful, these models need human eval and reinforcement learning through human feedback (RLHF) during pre-training, fine-tuning, and production evaluations. This is the main innovation that’s enabled ChatGPT to get such a large headstart among competition. At Scale, our products include the Generative AI Data Engine, SGP, Donovan, and others that power the most advanced LLMs and generative models in the world through world-class RLHF, human data generation, model evaluation, safety, and alignment. The data we are producing is some of the most important work for how humanity will interact with AI. At the foundation of these products is the Platform Engineering team. In this role, you will support the design and development of shared platforms used across Scale. This includes designing our foundational data platforms and lifecycle, architecting Scale’s core cloud infrastructure and orchestration stack, and redefining how engineers develop, build, test, and deploy software at Scale. You’ll also get widespread exposure to the forefront of the AI race as Scale sees it in enterprises, startups, governments, and large tech companies. You will: Drive the design, and implementation of our foundational platforms and systems, working closely with stakeholders and internal customers to understand and refine requirements. Collaborating with cross-functional teams to define, design, and deliver new features. Proactively identifying opportunities for, and driving improvements to, current p

Tenstorrent is leading the industry on cutting-edge AI technology, revolutionizing performance expectations, ease of use, and cost efficiency. With AI redefining the computing paradigm, solutions must evolve to unify innovations in software models, compilers, platforms, networking, and semiconductors. Our diverse team of technologists have developed a high performance RISC-V CPU from scratch, and share a passion for AI and a deep desire to build the best AI platform possible. We value collaboration, curiosity, and a commitment to solving hard problems. We are growing our team and looking for contributors of all seniorities. As a Director, Strategy & Solutions in our GTM team, this role defines how Tenstorrent shows up in the market for AI/ML workloads—from positioning and messaging to real customer solutions. Sitting at the intersection of product, sales, engineering, and marketing, this role turns deep technical capability into clear, compelling value across industries and use cases. This role is hybrid OR remote, based out of The United States. We welcome candidates at various experience levels for this role. During the interview process, candidates will be assessed for the appropriate level, and offers will align with that level, which may differ from the one in this posting. Who You Are Experienced at connecting complex AI/ML systems to real customer outcomes and business value. Comfortable acting as a technical storyteller for developers, architects, and executive audiences. Naturally curious and forward-looking about customer workloads, competitive dynamics, and emerging AI trends. What We Need Ownership of GTM positioning and messaging for Tenstorrent’s AI hardware, software stack, and solutions. Development of application - and vertical-specific value propositions across enterprise, cloud, and regulated markets. Value proposition & GTM strategy, including creation of technical collateral (whitepapers, sales decks, benchmarks, dem

Tenstorrent is leading the industry on cutting-edge AI technology, revolutionizing performance expectations, ease of use, and cost efficiency. With AI redefining the computing paradigm, solutions must evolve to unify innovations in software models, compilers, platforms, networking, and semiconductors. Our diverse team of technologists have developed a high performance RISC-V CPU from scratch, and share a passion for AI and a deep desire to build the best AI platform possible. We value collaboration, curiosity, and a commitment to solving hard problems. We are growing our team and looking for contributors of all seniorities. As a Manager, Strategy & Solutions in our GTM team, this role defines how Tenstorrent shows up in the market for AI/ML workloads—from positioning and messaging to real customer solutions. Sitting at the intersection of product, sales, engineering, and marketing, this role turns deep technical capability into clear, compelling value across industries and use cases. This role is hybrid OR remote, based out of The United States. We welcome candidates at various experience levels for this role. During the interview process, candidates will be assessed for the appropriate level, and offers will align with that level, which may differ from the one in this posting. Who You Are Experienced at connecting complex AI/ML systems to real customer outcomes and business value. Comfortable acting as a technical storyteller for developers, architects, and executive audiences. Naturally curious and forward-looking about customer workloads, competitive dynamics, and emerging AI trends. What We Need Ownership of GTM positioning and messaging for Tenstorrent’s AI hardware, software stack, and solutions. Development of application - and vertical-specific value propositions across enterprise, cloud, and regulated markets. Value proposition & GTM strategy, including creation of technical collateral (whitepapers, sales decks, benchmarks, demo

About Graphcore At Graphcore, we’re building the future of AI compute. We’re a team of semiconductor, software and AI experts, with deep experience in creating the complete AI compute stack - from silicon and software to infrastructure at datacenter scale. As part of the SoftBank Group, backed by significant long-term investment, we are delivering key technology into the fast-growing SoftBank AI ecosystem.To meet the vast and exciting AI opportunity, Graphcore is expanding its teams around the world.We are bringing together the brightest minds to solve the toughest problems, in a place where everyone has the opportunity to make an impact on the company, our products and the future of artificial intelligence . Job Summary Join our dynamic Software Infrastructure team and take a pivotal role in scaling and managing our infrastructure. You will develop essential tools and services that empower our broader software team. Your contributions will enhance the build, test, deployment, and productisation processes of our Machine Learning Software components. Work with our High-Performance Computing (HPC) AI platforms and gain invaluable experience in distributed systems The Team The Software Infrastructure team provides critical platforms and services for software development teams across the business. Our responsibilities include managing the CI platform and services, build engineering, component integration, and packaging and release systems. We operate in squads, fostering a culture of service ownership and empowerment for our engineers. We focus on long-term engineering solutions and strive to eliminate toil wherever possible. Responsibilities and Duties Develop, own, and maintain tools and services to support AI research and engineering teams Deploy and maintain services with Kubernetes and Docker Manage our Cloud Infrastructure using tools such as Terraform Candidate Profile Essential: