Principal Customer Engineer, Cloudflare

• Experience: Experience in a customer-facing technical role, such as Solutions Engineering, Customer Engineering, Professional Services, Sales Engineering, Technical Account Management, or as a Forward Deployed Engineer (years of experience required will vary based on Associate, Senior, Staff, or Principal leveling). Experience working with startups, AI companies, digital-native businesses, or as part of a startup engineering team is strongly valued
• Startup Ecosystem Network: An established network within incubators, accelerators, venture capital, and the broader startup scene is highly desirable, along with the drive to take on business development activities and open doors to new relationships
• Architectural Mindset: Ability to white-board, design, and articulate complex enterprise, startup, AI application, agent, network, and security architectures clearly
• Consultative & Advisory Skills: Excellent communication skills with the ability to translate deeply technical concepts into business outcomes for both hands-on engineers and C-level executives, founders, and technical leaders
• Commercial Mindset: Proven track record of operating in a quota-carrying or revenue-aligned environment, with a strong understanding of SaaS metrics, business value translation, and enterprise, mid-market, or startup sales cycles
• Communication: Exceptional presentation and stakeholder management skills, capable of bridging the gap between deep technical implementation details and high-level C-suite business strategy. Business fluency in German is required
• Technical Breadth: We do not expect every candidate to be an expert in every domain. Qualified candidates will demonstrate depth in at least four of the technical areas below:
• Internet fundamentals: Deep understanding of how the Internet works, including OSI Model layers 1–7, BGP, GRE, TCP/UDP, DNS (authoritative and recursive), HTTP(S), and SSL/TLS
• Security: Expertise in the security of Internet properties, including WAF, Bot Management, Firewalls, Rate Limiting, (M)TLS, Zero Trust, and SASE concepts
• Performance: Expertise in the performance of Internet properties, including speed, latency, caching, video streaming, HTTP/2, and TLS 1.3
• AI Engineering: Solid grounding in AI model fundamentals (model size, context length, reasoning models, fine-tuning versus prompting, and matching the right model to the job). Familiarity with common agent patterns, including knowing when a simple workflow beats an agent, and with open agent frameworks and standards such as MCP. Understanding of how to evaluate and operate AI systems in production
• AI-Augmented Workflows: Familiarity with prompt engineering, building prototypes with coding agents, AI-assisted scripting and log analysis, and workflow automation to augment everyday CE workflows
• Coding/Scripting: Proficiency in Python, JavaScript, Bash, Lua, Go, or similar languages to write custom integration scripts, API connectors, and edge computing functions
• Developer Platform Fluency: Experience designing, building, deploying or scaling applications using RESTful/GraphQL APIs, SDKs, webhooks, and developer tooling in cloud-native environments. Familiarity with infrastructure-as-code (Terraform, Pulumi), CI/CD pipelines, and observability for developer-led deployments

Desirable

• The Customer Engineer (CE) is the core driver of our technical go-to-market strategy: a trusted technical advisor and primary architect of the customer journey
• You will bridge the gap between technical strategy and business value
• You'll guide startup and AI customers from the first conversation about their AI ambitions through technical validation, production deployment, and long-term adoption and expansion
• Sitting within the GTM organization and reporting to a Customer Engineering Leader, you will not hand off your customers once an initial agreement is reached
• Instead, you will operate as a quota-carrying technologist, leveraging AI-augmented workflows to eliminate administrative toil so you can focus on high-value architectural design and driving measurable business outcomes across the Startup AI segment
• Technical Discovery & Validation: Partner closely with Account Executives to lead technical deep-dive discovery and uncover what kind of AI problem a customer actually has
• It might be building AI products and agents, governing how their people and agents use AI, or protecting internet-facing applications from AI-driven threats and traffic
• Turn that into a sequenced plan rather than a feature tour
• Capture business requirements and map startup and AI customer infrastructure (DNS, CDN, Zero Trust, Network Security, serverless and edge compute) to fit-for-purpose Cloudflare architectures and bespoke solutions
• Define scope, success criteria, and technical evaluation plans for Proofs of Concept (PoCs) and Technical Validations, anchored in measurable quality, latency, and cost targets rather than subjective impressions
• Rapidly build working, customer-specific prototypes
• Deliver tailored technical presentations, architectural diagrams, and demonstrations that show how Cloudflare solves specific performance, security, reliability, and scale challenges
• Proactively address complex technical objections, security compliance questions, and edge-case architectural requirements during the sales cycle
• Take accountability for a suitable solution deployment strategy (Customer, Partner or Cloudflare Professional Services) being an integral part of all proposals
• Customer Adoption & Value Realization: Oversee technical onboarding and implementation without executing it yourself, serving as the primary executive and engineering contact for the customer
• Design structured migration and onboarding blueprints tailored to the customer's environment (e.g
• DNS migrations, Zero Trust rollouts, WAF tuning guidance)
• Act as the lead consultant for customer engineering teams, walking them step-by-step through configuration best practices
• Guide customers in taking AI applications and agents from prototype to production in a way that is reliable, safe, and affordable
• That covers durable state and failure recovery for long-running agents; secure agent design such as defenses against prompt injection, scoped access, and human approval for sensitive actions; and the right model choices for each task
• After go-live, help customers keep AI workloads healthy through tracing, quality and cost monitoring, and safe rollout of model and prompt changes, feeding production learnings back into evaluation
• Partner with Account Executives to own discovery, demos, onboarding, technical health, risk, and expansion strategy
• Proactively monitor customer health scores and telemetry to ensure rapid time-to-value, resolve integration bottlenecks, and reduce deployment risk as customers move from early-stage development to production scale
• Commercial Accountability & Expansion: Carry a variable quota tied directly to new business acquisition and/or ongoing account growth
• Be commercially accountable for ensuring deep platform adoption, retaining revenue, and identifying strategic cross-sell and up-sell opportunities based on product usage data and the evolving needs of startup and AI customers
• Translate AI spend into clear business cases, such as cost per task or per resolved request
• Lead technical Quarterly Business Reviews (QBRs) to translate platform capabilities into return on investment for founders, C-level executives, and engineering leaders
• Ecosystem & Business Development: Help build and grow Cloudflare's presence in the startup and AI ecosystem
• Develop relationships with incubators, accelerators, venture capital firms, founder communities, and developer meetups to generate new pipeline alongside Account Executives
• Represent Cloudflare at startup events, demo days, and hackathons, and identify high-potential AI startups early in their journey
• Trusted Advisory: Act as a trusted technical advisor throughout the entire customer lifecycle, maintaining a continuous, deep relationship with founders, CTOs, engineering leaders, and other key stakeholders from initial onboarding through maturity, renewal, and expansion
• Provide thought partnership on architecture, agent design, AI governance and compliance (e.g
• GDPR, EU AI Act, data residency), security posture, and deployment confidence
• Identify potential deployment risks or integration bottlenecks early, and provide remediation strategies to de-risk customer outcomes
• AI Orchestration & Workflow Automation: Use AI agents, coding agents, Large Language Models (LLMs), and internal platforms as a default way of working
• Automate routine tasks such as meeting preparation, RFP/Security Questionnaire responses, sandbox provisioning, demo setup, basic telemetry monitoring, and internal/external documentation, so you have more time for strategic customer advisory
• Apply AI-assisted workflows to support customer engineering teams and improve the speed and quality of technical validation
• Share hands-on learnings and gaps with product teams as a direct feedback channel
• Education & Enablement: Partner closely with the Enablement Team to design, build, and govern technical resources
• Define, document, and educate both internal teams and customers on deliverables such as Standard Operating Procedures (SOPs), architectural best practices, and technical guides to continuously raise the technical baseline across the organization
• Support technical enablement for startup and AI customers through workshops, code samples, documentation, and developer onboarding