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Enterprise Sales Engineer - West & Central

United States · Job Posted May 16, 2026
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Job Description

At DevRev, Enterprise Sales Engineers are customer-obsessed technical professionals who bridge the gap between cutting-edge product innovation and real customer needs. As a trusted advisor, you’ll support direct sales cycles enabling customers to fully understand, evaluate, and adopt DevRev solutions. As a core member of the sales team, you’ll partner with Enterprise Account Executives to plan and execute sales campaigns. You’ll blend technical acumen with storytelling, preparing and conducting tailored demos, guiding evaluations, and shaping proposals. In close collaboration with Sales, Product, and Engineering you’ll ensure customers and partners experience DevRev not just as a product, but as a strategic platform powering their success. DevRev is at the tip of the spear of the AI revolution. We encourage our employees to embrace AI solutions to make their everyday work more efficient. At DevRev, you’ll experience the first AI powered sales organization using our revolutionary products, and use leading foundational models and services to make your work go further.

Job Responsibility

  • Provide expert technical guidance throughout the sales cycle, addressing customer questions with clarity and confidence
  • Partner with Account Executives to understand use cases, uncover pain points, and design tailored solutions
  • Deliver engaging product demos, PoCs, and proofs of concept that showcase DevRev’s differentiators and business impact
  • Contribute to RFP/RFI responses and create compelling proposals aligned to customer needs
  • Build strong relationships as a trusted technical advisor and ensure smooth handoffs to Customer Success
  • Translate business challenges into DevRev-aligned architectures and scalable solutions
  • Support customization, integrations, and configurations in collaboration with Product and Engineering
  • Provide early-stage onboarding support and issue resolution when needed
  • Deliver workshops, bootcamps, certifications, and co-create joint service offerings
  • Train sales teams on product updates, technical capabilities, and competitive positioning
  • Develop technical playbooks, demo assets, guides, and case studies
  • Monitor competitor offerings and share insights to influence strategy
  • Mentor peers and foster a culture of collaboration and learning

Requirements

  • Bachelor’s or Master’s degree in Computer Science, Engineering, or related field
  • 5+ years of experience in B2B SaaS Sales/Solution Engineering focused on Enterprise accounts
  • Proven track record delivering demos, workshops, technical proposals, and proofs of value
  • Familiarity with enterprise sales methodologies (e.g., Command of the Message, MEDDICC)
  • Strong discovery and consultative selling mindset
  • Excellent communication and storytelling abilities, comfortable with both technical and executive stakeholders
  • Skilled presenter and whiteboard communicator
  • Effective cross-functional collaborator across Sales, Product, and Customer Success
  • Adaptive in unstructured environments
  • Flexible team player who embraces all tasks
  • Strong technical acumen across APIs, integrations, DevOps, cloud platforms, and modern SaaS stacks
  • Experience consuming APIs and webhooks (e.g., Postman) and configuring integrations
  • Familiarity with major cloud platforms (AWS, Azure, GCP) and networking concepts
  • Experience building with generative code solutions (Cursor, Claude Code, Augment Code, etc.)
  • Experience and understanding of LLMs/GenAI models, ML, and applied agentic solutions
  • Willingness to travel up to 50% as needed
  • Ecosystem Experience with at least 3 of the following: CRM: Salesforce Sales Cloud, HubSpot, Zoho, Zendesk, Salesforce Service Cloud, Freshdesk, Intercom, Microsoft Dynamics, Monday
  • Service Desk: ServiceNow, Freshservice, Jira Service Management
  • DevOps: Jira, Linear, GitHub, GitLab, Azure DevOps
  • Documentation: SharePoint, OneDrive, Notion, Google Drive
  • Data Lake/Data Warehouse: Snowflake, BigQuery, Databricks

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