Forward Deployed Engineer

• 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

Benefits

• Paid parental leave: 8 weeks for all parents, 16 weeks for birthing parents
• Unlimited paid time off, plus 3 global VeeaMe Days for self-care
• Medical, dental, and vision coverage from day one
• 401(k) retirement plan with matching contributions up to annual limits
• Fertility, adoption, and surrogacy support through Maven, plus paid volunteer time
• Mental health support, therapy sessions, and digital wellness tools via SupportLinc EAP
• Legal services, identity protection, and supplemental health insurance options
• AirVet: 24/7 virtual veterinary care at no cost
• Professional training and education, including courses and workshops, internal meetups, and unlimited access to our online learning platforms (LinkedIn Learning, Athena, O’Reilly) and mentoring through our MentorLab program
• Tax-advantaged spending accounts for healthcare, dependent care, and commuting

• Strong understanding of APIs, system integration, SQL/NoSQL data stores, and structured or unstructured data
• Experience working across hybrid environments, including cloud, private cloud, and on-premises systems
• Experience building and shipping practical technical solutions, such as scripts, integrations, data pipelines, classifiers, automations, or internal tools
• High ownership, strong critical thinking, and the ability to bring structure to complex problems without a clear playbook
• Working knowledge of data security, privacy, and regulatory topics across industries and geographies
• Ability to read unfamiliar code, understand running systems quickly, and guide targeted changes when needed
• 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
• Hands-on experience with Kubernetes, containers, Linux, and cloud platforms such as AWS, Azure, or Google Cloud
• 4–7+ years of experience in technical, customer-facing roles, such as forward-deployed engineering, solutions engineering, platform engineering, or technical consulting
• Ability to translate unclear security, privacy, compliance, or business needs into a clear technical plan
• Strong software engineering skills, with fluency in at least one programming language such as Python, Go, or TypeScript
• Experience building or heavily using AI agents, agentic coding assistants, MCP, or RAG systems
• Experience with enterprise data platforms such as Snowflake, Databricks, or BigQuery
• Familiarity with regulatory frameworks such as GDPR, SOC 2, or ISO 27001
• Experience with DSPM, CSPM, DLP, data governance, privacy platforms, or related security domains
• Knowledge of access control, encryption, masking, or data protection controls in enterprise data systems