Customer AI & Automation Engineer

About Vectra AI 

Vectra AI is the leader in AI-driven threat detection and response for hybrid and multi-cloud enterprises. The Vectra AI Platform brings together signal across public cloud, SaaS, identity, and data center networks to help security teams prioritize, investigate, and respond to advanced cyber-attacks. 

The Role 

Vectra AI is building a proactive, intelligent customer experience model that helps customers deploy, adopt, realize value, and expand with less dependency on manual intervention. These are the next steps in our customer experience that pair both human touch and automated enablement for our customers. The Customer AI & Automation Engineer will create the technical foundation that makes this model scalable, reliable, and measurable. 
 

The Customer AI & Automation Engineer designs, builds, tests, and operates the workflows, integrations, and AI agents that power customer journeys across Salesforce, HubSpot, Pendo, enablement and product signals. This is a hands-on builder role for someone who combines systems thinking, data fluency, and practical business judgment. 

The role supports Technical Account Managers (TAMs), Sales Engineers (SEs) responsible for post-sales account management, Professional Services (PS), Technical Support, and broader Digital Success initiatives. 

Your Impact 

• Build and maintain customer lifecycle workflows across HubSpot, Salesforce, Pendo, and connected customer systems. 

• Design and operationalize AI agents for journey operations, signal detection, next-best-action recommendations, support guidance, and customer insight. 

• Translate requirements from Lifecycle Strategy, Customer Success, Support, SE, Product, Enablement, and Marketing into scalable automation and orchestration logic. 

• Technical Account Management: Automate account health preparation, technical success plan updates, recurring health checks, action tracking, and customer review preparation. 

• SE post-sales account management: Support technical account oversight, deployment and adoption reviews, product utilization analysis, technical risk identification, and follow-through on customer actions. 

• Professional Services: Streamline onboarding, deployment planning, readiness checks, project updates, and delivery documentation. 

• Technical Support: Improve case triage, troubleshooting, knowledge retrieval, and resolution workflows. 

• Digital Success: Build scalable onboarding, adoption guidance, customer health monitoring, and proactive outreach workflows. 

• Develop integrations and data flows that connect customer, product, support, engagement, and enablement signals. 

• Establish testing, QA, monitoring, exception handling, observability, and rollback procedures for automations and AI-enabled workflows. 

• Create operational reporting that surfaces journey enrollment, workflow health, drop-offs, exceptions, adoption signals, and agent performance. 

• Support the Customer Lifecycle Council with technical feasibility assessments, implementation estimates, and evidence on what is working or breaking. 

• Map customer journeys and internal processes, including handoffs between teams, and prioritize use cases based on customer impact, effort saved, feasibility, and business value. 

• Integrate knowledge platforms and internal product systems into agent workflows using APIs and orchestration tools. 

• Define clear operational ownership and human approval steps for agent actions, supported by audit trails and data protection controls. 

• Improve production workflows using feedback and usage data; document solutions and train teams to use and maintain them. 

What You Will Bring 

• Demonstrated experience designing, building, deploying, and operating production-scale AI agents using both OpenAI GPT and Anthropic Claude models. 

• Hands-on experience selecting and orchestrating models for different tasks, including tool use, retrieval, structured outputs, workflow execution, evaluation, observability, permissions, and human escalation. 

• Proven ability to move agents beyond prototype stage into reliable, governed enterprise use cases with measurable business outcomes. 

• Experience building complex workflow automation and systems integrations in a customer-facing, revenue, marketing operations, customer operations, or product operations environment. 

• Strong analytical and troubleshooting skills, with the ability to trace a customer outcome through data, systems, workflow logic, and operational ownership. 

• A disciplined approach to testing, data quality, permissions, exception handling, and change management. 

• Ability to translate ambiguous business requirements into simple, scalable technical solutions and communicate clearly across technical and non-technical teams. 

• Proficiency in Python or JavaScript/TypeScript and experience working with webhooks and structured data. 

• Hands-on experience with prompt design and retrieval-augmented generation. 

Preferred Qualifications 

• Experience operating multi-model agent environments, including practical knowledge of GPT and Claude strengths, limitations, cost, latency, safety, and evaluation considerations. 

• Experience with customer lifecycle, digital customer success, product-led growth, or customer marketing motions. 

• Familiarity with customer health, telemetry, product usage, support, and enablement data. 

• Experience working in B2B SaaS, cybersecurity, or another complex enterprise technology environment. 

• Practical experience with Salesforce, HubSpot, Pendo, support platforms, CDPs or data warehouses, APIs, and automation tools. 

• Familiarity with Jira, MuleSoft, Forethought, or comparable platforms. 

• Understanding of technical account management, post-sales account management, implementation, and service delivery processes. 

Success Measures 

• Reduced manual effort across targeted workflows. 

• Shorter cycle times and faster customer onboarding and time to value. 

• Increased product adoption and effective digital engagement. 

• Earlier identification and follow-through on customer risks. 

• Improved efficiency and account coverage for TAMs and post-sales SEs. 

• Reliable agent execution and measurable customer experience improvements.