Forward Deployed Engineer
Forward Deployed Engineer owning technical outcomes for strategic customer deployments of Veeam's Securiti AI data security platform — deploying, integrating, and scaling it across cloud, hybrid, and on-prem environments. Hands-on work with Kubernetes, containers, Linux, AWS/Azure/GCP, APIs, and Python/Go/TypeScript.
- Compensation
- $137.2K–$228.5K / yr
- Location
- San Jose, United States
- Work setup
- Onsite
- Seniority
- Not specified
- Employment
- Not specified
- Experience
- 7+ years
- Category
- Solutions engineering
- Posted
Skills
Must have
- 4–7+ years in technical, customer-facing roles (forward-deployed engineering, solutions engineering, platform engineering, or technical consulting)
- Fluency in at least one programming language such as Python, Go, or TypeScript
- Experience building and shipping practical technical solutions (scripts, integrations, data pipelines, classifiers, automations, internal tools)
- Ability to read unfamiliar code, understand running systems quickly, and guide targeted changes
- Hands-on experience with Kubernetes, containers, Linux, and cloud platforms (AWS, Azure, or Google Cloud)
- Experience working across hybrid environments (cloud, private cloud, on-premises)
- Strong understanding of APIs, system integration, SQL/NoSQL data stores, and structured or unstructured data
- Experience using AI-native developer tools, agents, and automation
- Strong customer presence; able 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 ability to bring structure to complex problems without a clear playbook
Nice to have
- 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
Full description
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