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Forward Deployed Engineer (Python, TypeScript)

Veeam is the Data and AI Trust Company, specializing in helping organizations ensure their data and AI are fully understood, secured, and resilient to enable the acceleration of safe AI at scale. As the market leader in both data resilienc…

veeam · На сервисе с: 03.10.26 21:15

Зарплата не указанаСШАКанадаSan JoseГибрид
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Veeam is the Data and AI Trust Company, specializing in helping organizations ensure their data and AI are fully understood, secured, and resilient to enable the acceleration of safe AI at scale. As the market leader in both data resilience and data security posture management, Veeam is built for the convergence of identity, data, security, and AI risk. Headquartered in Seattle with offices in more than 30 countries, Veeam protects over 550,000 customers worldwide, who trust Veeam to keep their businesses running. Join us as we go fearlessly forward together, growing, learning, and making a real impact for some of the world’s biggest brands.

About the Role

As a Forward Deployed Engineer, you will be the technical owner for strategic customer deployments of the Securiti AI platform within Veeam. You will work directly with customers to deploy, integrate, and scale the platform across complex cloud, hybrid, and on-premises environments.

  • ✨ This role will be 3 days in office at our San Jose, CA location! ✨

You will help customers turn complex data and AI environments into clear security, privacy, governance, and AI readiness outcomes. This is a hands-on engineering role where you will build integrations, automate workflows, troubleshoot issues, and adapt the platform to fit real customer needs.

What You'll Do

  • Own the technical outcome for customer accounts, from first deployment through scaled, everyday use
  • Deploy and configure the platform across hybrid environments, including AWS, Azure, Google Cloud, private cloud, and on-premises systems
  • Connect the platform to customer data systems, identity providers, reporting tools, and business workflows
  • Configure, tune, and troubleshoot core deployment components, including Kubernetes, containers, Linux, and cloud infrastructure
  • Build and operate integrations using APIs, including SSO/SAML/OIDC, SIEM, ITSM, data platforms, and downstream reporting or remediation systems
  • Translate customer goals into technical plans that support data discovery, classification, governance, privacy, and AI security outcomes
  • Adapt platform behavior when standard configuration does not fully match the customer’s data, risk model, or operating process
  • Build production-grade solutions, including data pipelines, custom classifiers, automations, integrations, and agent-based workflows
  • Use AI-native tools and agents to automate repeatable work, improve delivery quality, and increase your impact
  • Diagnose complex issues across data, deployment, and integration layers using observability tools and structured problem-solving
  • Lead technical sessions with customer teams; partner with Sales Engineering, Product, and Engineering to support POCs, resolve issues, and share field learnings
  • This role will be 3 days in office at our San Jose, CA location! 

What You'll Bring

  • 4–7+ years of experience in technical, customer-facing roles, such as forward-deployed engineering, solutions engineering, platform engineering, or technical consulting
  • Strong software engineering skills, with fluency in at least one programming language such as Python, Go, or TypeScript
  • Experience building and shipping practical technical solutions, such as scripts, integrations, data pipelines, classifiers, automations, or internal tools
  • Ability to read unfamiliar code, understand running systems quickly, and guide targeted changes when needed
  • Hands-on experience with Kubernetes, containers, Linux, and cloud platforms such as AWS, Azure, or Google Cloud
  • Experience working across hybrid environments, including cloud, private cloud, and on-premises systems
  • Strong understanding of APIs, system integration, SQL/NoSQL data stores, and structured or unstructured data
  • Experience using AI-native developer tools, agents, and automation to work faster and improve quality
  • Strong customer presence, with the ability to build trust with executives, business stakeholders, and technical teams
  • Ability to translate unclear security, privacy, compliance, or business needs into a clear technical plan
  • Working knowledge of data security, privacy, and regulatory topics across industries and geographies
  • High ownership, strong critical thinking, and the ability to bring structure to complex problems without a clear playbook

Bonus Skills

  • Experience with DSPM, CSPM, DLP, data governance, privacy platforms, or related security domains
  • Experience building or heavily using AI agents, agentic coding assistants, MCP, or RAG systems
  • Familiarity with regulatory frameworks such as GDPR, SOC 2, or ISO 27001
  • Experience with enterprise data platforms such as Snowflake, Databricks, or BigQuery
  • Knowledge of access control, encryption, masking, or data protection controls in enterprise data systems

What you'll get

  • Unlimited paid time off, 12 paid holidays including 4 global VeeaMe Days for self-care and 24 paid volunteer hours annually through Veeam Cares
  • Paid parental leave: 8 weeks for all parents, 16 weeks for birthing parents
  • Medical, dental, and vision coverage starting on your first day
  • Mental health support, therapy sessions, and digital wellness tools via our Employee Assistance Program
  • 401(k) retirement plan with company matching contributions
  • Fertility, adoption, and surrogacy support through Maven, plus paid volunteer time
  • AirVet: 24/7 virtual veterinary care at no cost
  • Legal services, identity protection, and supplemental health insurance options
  • Tax-advantaged spending accounts for healthcare, dependent care, and commuting
  • Opportunities to learn and grow through on-demand libraries (LinkedIn Learning, O’Reilly), mentoring, workshops, and learning events like our annual Global Day of Learning

Pay Transparency

Veeam is committed to pay transparency and equitable compensation. For this role, the compensation range below reflects the expected total target compensation (TTC), inclusive of base pay and a competitive performance-based bonus. For roles with a commission plan, the compensation range represents On Target Earnings (OTE), which includes base salary plus variable commission. When determining compensation, Veeam takes into consideration factors such as experience, education, skills, and geographic zone. Offers are typically made below the midpoint of the range.

In addition to compensation, Veeam provides a comprehensive benefits package, including health coverage, retirement plans, and unlimited time off.

Compensation Range (TTC / OTE)
$137,160—$228,480 USD

Veeam Software is an equal opportunity employer and does not tolerate discrimination in any form on the basis of race, color, religion, gender, age, national origin, citizenship, disability, veteran status or any other classification protected by federal, state or local law. All your information will be kept confidential.

Personal data collected during the recruitment process will be processed in accordance with our Recruiting Privacy Notice, which explains how your information is collected, used, and handled in connection with hiring activities. By applying for this position, you consent to this processing. 

By submitting your application, you confirm that the information provided, including any supporting documents, is complete and accurate to the best of your knowledge. Any misrepresentation, omission, or falsification may result in disqualification from consideration or, if discovered after employment begins, termination of employment.

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Senior Forward Deployed Engineer

veeamНа сервисе с: 03.10.26 21:20
Зарплата не указанаСШАMelbourneГибрид

Veeam is the Data and AI Trust Company, specializing in helping organizations ensure their data and AI are fully understood, secured, and resilient to enable the acceleration of safe AI at scale. As the market leader in both data resilience and data security posture management, Veeam is built for the convergence of identity, data, security, and AI risk. Headquartered in Seattle with offices in more than 30 countries, Veeam protects over 550,000 customers worldwide, who trust Veeam to keep their businesses running. Join us as we go fearlessly forward together, growing, learning, and making a real impact for some of the world’s biggest brands.

About the Role 

As a Senior Forward Deployed Engineer, you will be the technical owner for some of the most complex and strategic customer accounts. You will lead the technical approach, make clear decisions in ambiguous situations, and help customers get real value from the platform in complex enterprise environments. 

You will work across deployment, integration, automation, and solution design. You will also handle deep technical escalations and build reusable patterns, tools, and playbooks that help the wider Forward Deployed Engineering team move faster and deliver more consistently. 

This is a hands-on senior engineering role. You will work directly with customer executives, security and privacy leaders, business stakeholders, and technical teams. You will turn complex data, security, privacy, and AI needs into practical solutions that can scale. 

What You'll Do 

  • Own technical delivery for the most complex customer accounts, from deployment through scaled, everyday use 
  • Lead deployments across hybrid environments, including cloud, on-premises, Kubernetes, containers, Linux, and related infrastructure 
  • Define solution architecture for customers with complex data estates, security needs, and business requirements 
  • Adapt platform behavior when standard configuration does not fully match the customer’s data, workflows, or risk model 
  • Build and operate integrations across customer systems, including identity, SIEM, ITSM, data platforms, APIs, and downstream tools 
  • Diagnose and resolve deep technical issues across data, deployment, infrastructure, and integration layers 
  • Build reusable agents, automations, tools, and playbooks that help the broader FDE team deliver faster and with higher quality 
  • Turn manual customer outcomes into repeatable workflows for remediation, alerting, reporting, and operational follow-up 
  • Lead architecture and design sessions with customer executives, security and privacy leaders, business teams, and engineers 
  • Mentor other FDEs by reviewing solutions, sharing patterns, and helping unblock complex technical work 
  • Partner with Sales Engineering, Product, and Engineering on strategic POCs, customer escalations, and product feedback from the field 

 

What You'll Bring 

  • 8–12+ years of experience in deeply technical, customer-facing roles, such as forward-deployed engineering, solutions engineering, platform engineering, or technical consulting 
  • Strong software engineering skills in at least one language, such as Python, Go, or TypeScript, with the ability to read unfamiliar code and understand complex systems quickly 
  • Hands-on experience with Kubernetes, containers, Linux, and cloud platforms such as AWS, Azure, or Google Cloud 
  • Experience deploying and operating solutions across complex cloud, hybrid, and on-premises enterprise environments 
  • Strong understanding of APIs, system integration, SQL/NoSQL data stores, and structured or unstructured data 
  • Experience building practical technical solutions, such as data pipelines, custom classifiers, integrations, automations, agents, or internal tools 
  • Strong fluency with AI-native developer tools, agents, and automation, including creating reusable workflows that help others move faster 
  • Strong customer presence, with the ability to build trust with executives, business leaders, and engineering teams 
  • Working knowledge of data security, privacy, and regulatory topics across industries and geographies 
  • High ownership, strong critical thinking, and the ability to bring structure to complex problems without a clear playbook 

 

Bonus Skills 

  • Experience with DSPM, CSPM, DLP, data governance, privacy platforms, or related security domains 
  • Experience building or heavily using AI agents, agentic coding assistants, MCP, or RAG systems 
  • Familiarity with regulatory frameworks such as GDPR, SOC 2, or ISO 27001, especially across multiple geographies 
  • Experience with enterprise data platforms such as Snowflake, Databricks, or BigQuery 
  • Knowledge of access control, encryption, masking, or other data protection controls in enterprise data systems 
  • Experience mentoring senior technical contributors or setting delivery standards in fast-paced, distributed teams 

 

#LI-VG1
#LI-SK1

 

Veeam Software is an equal opportunity employer and does not tolerate discrimination in any form on the basis of race, color, religion, gender, age, national origin, citizenship, disability, veteran status or any other classification protected by federal, state or local law. All your information will be kept confidential.

Personal data collected during the recruitment process will be processed in accordance with our Recruiting Privacy Notice, which explains how your information is collected, used, and handled in connection with hiring activities. By applying for this position, you consent to this processing. 

By submitting your application, you confirm that the information provided, including any supporting documents, is complete and accurate to the best of your knowledge. Any misrepresentation, omission, or falsification may result in disqualification from consideration or, if discovered after employment begins, termination of employment.

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DevSecOps

veeamНа сервисе с: 03.10.26 21:16
Зарплата не указанаСШАКанадаSan Jose

Veeam is the Data and AI Trust Company, specializing in helping organizations ensure their data and AI are fully understood, secured, and resilient to enable the acceleration of safe AI at scale. As the market leader in both data resilience and data security posture management, Veeam is built for the convergence of identity, data, security, and AI risk. Headquartered in Seattle with offices in more than 30 countries, Veeam protects over 550,000 customers worldwide, who trust Veeam to keep their businesses running. Join us as we go fearlessly forward together, growing, learning, and making a real impact for some of the world’s biggest brands.

About the Role

Securiti's platform processes billions of data events per day across hundreds of enterprise clouds. As a DevSecOps Engineer, you will build and maintain the invisible infrastructure that makes this scale possible—ensuring developers can ship features daily while maintaining fortress-level security.

You will be responsible for designing self-healing deployment pipelines that turn infrastructure into code, security into automation, and complexity into reliability. Your work ensures that when a customer onboards petabytes of data, our platform scales transparently—without manual intervention.

Responsibilities

  • Security-First Infrastructure: Architect and implement infrastructure-as-code using Terraform and CloudFormation, ensuring every deployment follows zero-trust principles and least-privilege access models.

  • Kubernetes at Scale: Design and optimize our Kubernetes clusters to handle massive workloads, implementing intelligent autoscaling, pod security policies, and network segmentation that protects sensitive customer data.

  • Zero-Downtime Deployments: Build sophisticated CI/CD pipelines using ArgoCD, Spinnaker, and GitOps patterns that enable blue/green and canary deployments—allowing us to ship multiple times per day with zero customer impact.

  • Observability Engineering: Implement comprehensive monitoring and alerting using Prometheus, Grafana, and ELK, creating dashboards that surface anomalies before they become incidents.

  • Multi-Cloud Orchestration: Manage infrastructure across AWS, Azure, and GCP, building abstraction layers that allow our platform to run anywhere while maintaining consistent security postures.

  • Performance Under Fire: Be on-call to diagnose and resolve production issues in real-time, using your deep systems knowledge to troubleshoot complex distributed systems problems across the stack.

  • Automation-First Mindset: Write Python and Go tooling that automates repetitive operational tasks, turning hours of manual work into seconds of automated execution.

 

Requirements

  • Experience: 5+ years of software development with deep operational experience in cloud-native environments (AWS, Azure, GCP).

  •  Infrastructure as Code Mastery: Expert-level proficiency with Terraform or AWS CloudFormation, with a portfolio of reusable modules and patterns.

  • Container Orchestration: Production experience running Kubernetes at scale, including deep knowledge of networking, security contexts, and stateful workloads.

  • CI/CD Architecture: Hands-on experience designing GitOps-based deployment pipelines using tools like ArgoCD, Spinnaker, Jenkins, or GitHub Actions.

  • Development Skills: Professional coding ability in Python or Golang—you're not just configuring tools, you're building them.

  • Database Operations: Working knowledge of SQL (Postgres), NoSQL (MongoDB/Elasticsearch), and Graph databases (Neo4j, Neptune) for operational troubleshooting and performance tuning.

  • Linux & Networking Fundamentals: Deep understanding of Linux systems administration, bash scripting, network routing, load balancing, and service mesh architectures.

  • Monitoring & Observability: Experience implementing full-stack observability with metrics, logs, and traces using Prometheus, Grafana, ELK, or similar tooling.

 

Bonus Points

  • Security Certifications: AWS Security Specialty, CKS (Certified Kubernetes Security Specialist), or equivalent security-focused credentials.

  • Service Mesh Experience: Hands-on work with Istio, Linkerd, or Consul for advanced traffic management and zero-trust networking.

  • Chaos Engineering: Experience with fault injection frameworks (Chaos Monkey, Litmus) to build resilient systems.

  • GitOps Evangelism: You've championed GitOps practices and trained teams on declarative infrastructure patterns.

  • Cost Optimization: Track record of reducing cloud spend through intelligent resource management and architectural improvements.

 

 

What you'll get

  • Unlimited paid time off, 12 paid holidays including 4 global VeeaMe Days for self-care and 24 paid volunteer hours annually through Veeam Cares
  • Paid parental leave: 8 weeks for all parents, 16 weeks for birthing parents
  • Medical, dental, and vision coverage starting on your first day
  • Mental health support, therapy sessions, and digital wellness tools via our Employee Assistance Program
  • 401(k) retirement plan with company matching contributions
  • Fertility, adoption, and surrogacy support through Maven, plus paid volunteer time
  • AirVet: 24/7 virtual veterinary care at no cost
  • Legal services, identity protection, and supplemental health insurance options
  • Tax-advantaged spending accounts for healthcare, dependent care, and commuting
  • Opportunities to learn and grow through on-demand libraries (LinkedIn Learning, O’Reilly), mentoring, workshops, and learning events like our annual Global Day of Learning

Pay Transparency

Veeam is committed to pay transparency and equitable compensation. For this role, the compensation range below reflects the expected total target compensation (TTC), inclusive of base pay and a competitive performance-based bonus. For roles with a commission plan, the compensation range represents On Target Earnings (OTE), which includes base salary plus variable commission. When determining compensation, Veeam takes into consideration factors such as experience, education, skills, and geographic zone. Offers are typically made below the midpoint of the range.

In addition to compensation, Veeam provides a comprehensive benefits package, including health coverage, retirement plans, and unlimited time off.

Compensation Range (TTC / OTE)
$153,480—$255,720 USD

Veeam Software is an equal opportunity employer and does not tolerate discrimination in any form on the basis of race, color, religion, gender, age, national origin, citizenship, disability, veteran status or any other classification protected by federal, state or local law. All your information will be kept confidential.

Personal data collected during the recruitment process will be processed in accordance with our Recruiting Privacy Notice, which explains how your information is collected, used, and handled in connection with hiring activities. By applying for this position, you consent to this processing. 

By submitting your application, you confirm that the information provided, including any supporting documents, is complete and accurate to the best of your knowledge. Any misrepresentation, omission, or falsification may result in disqualification from consideration or, if discovered after employment begins, termination of employment.

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DataOps Intern

tabbyНа сервисе с: 03.10.26 18:46
Зарплата не указанаСаудовская АравияRiyadhОфис

About the role

About the company

Tabby builds financial products used by millions of users across the GCC. The infrastructure behind them runs at scale, under strict requirements for reliability, cost efficiency and regulatory compliance.

This is not a course and not a shadowing programme. It is an engineering role with real responsibility.

Context

The Data Platform team runs the infrastructure that AI, ML and data workloads at Tabby depend on: compute, orchestration, deployment, observability and cost control across cloud environments. The work sits between classic DevOps and the machine-learning side. The same clusters, pipelines and monitoring that keep a service alive also keep models trained, served and measured.

The internship is designed for strong early-career engineers who are comfortable in Linux and a cloud, and who already use AI tools in their own work rather than reading about them. Interns join the team, work on real production infrastructure under senior review and are expected to meet engineering standards from day one.


Responsibilities

What you will do

This is not a helper or ticket-closing role. Interns work on real production tasks under senior review.
  • Work with the cloud infrastructure (primarily GCP) and the bare-metal fleet that host our data, ML and AI workloads
  • Build and maintain CI/CD pipelines for services and models
  • Run and troubleshoot containerised workloads on Kubernetes
  • Set up and improve monitoring, alerting and logging, and act on what they show
  • Automate repetitive operational work with Python or Bash instead of repeating it
  • Support model training and inference workloads: environments, resources, deployment, cost
  • Investigate incidents in infrastructure and pipelines and help find root causes
  • Improve the reliability and cost efficiency of the platform
  • Work within SAMA regulatory requirements: in Saudi fintech, where data lives and who can reach it is part of the engineering problem, not paperwork someone else handles

What you will actually work with

Not a wish list. This is the stack the team runs today. Nobody is expected to arrive knowing all of it.
  • Data: CDC pipelines, BigQuery, Airflow
  • ML: Airflow, ClearML and similar orchestration and experiment tooling
  • AI: bare-metal GPU servers, vLLM, open-source models served in-house
  • Platform: GCP, Kubernetes, Linux, networking
  • Context: SAMA regulations

Qualifications

Required

  • Solid Linux fundamentals: filesystem, processes, permissions, networking basics, comfortable in the shell
  • Hands-on experience with at least one cloud provider, evidenced by something you actually built or deployed. We run on GCP, so GCP experience is the most directly useful, but AWS or Azure evidence counts: the concepts transfer, and we would rather have someone who has really built something on one cloud than someone who has clicked around ours
  • Understanding of networking: DNS, TCP/IP basics, load balancing, what happens between a request and a service
  • Working knowledge of containers, and enough Kubernetes to deploy and debug a workload
  • Familiarity with monitoring and observability concepts: metrics, logs, alerts and what makes an alert useful
  • Python or Bash sufficient to automate operational tasks
  • Experience with Git and standard development workflows
  • Real, current use of AI tools in your own engineering work: which tools, for what, and an informed view of which models suit which task. We would rather hear an honest comparison than a list of names
  • Structured thinking and attention to correctness
  • Open to constructive feedback
  • English sufficient for documentation and team communication

Strong plus

  • Infrastructure as code (Terraform or similar)
  • Experience running a CI/CD system end to end (GitLab CI, GitHub Actions or similar)
  • An observability stack in practice: Prometheus, Grafana or equivalents
  • Exposure to MLOps tooling: experiment tracking, model registries, feature stores, inference serving
  • Has tried to run an open-source model themselves (on a laptop, a rented GPU, anything) and can explain how LLMs actually work rather than just which API they called
  • Any experience with GPU workloads, or with the cost side of running them
  • Interest in platform design and developer experience

Eligibility

  • Saudi nationals only
  • We welcome both current students and fresh graduates
  • We expect a full-time level of engagement. The programme is not part-time. Students can align time for classes or exams with their mentor in advance, but performance, ownership and involvement are expected at a full-time level

Benefits

  • Six months, starting autumn 2026
  • Paid internship, funded by Tabby
  • Full integration into an engineering team
  • Distributed engineering team across multiple countries
  • A path to a junior role on the platform side afterwards. That is our intent and what we aim for, not a guarantee: it depends on how the internship goes
This internship is intentionally demanding and designed for candidates aiming for fast professional growth in infrastructure and AI platform engineering.

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