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Render is seeking its first Forward Deployed Engineer to serve as a dedicated technical partner for the company's most strategic customers and fastest-growing AI startups. The role balances two core motions: providing white-glove, concierge-level technical engagement with top-tier accounts, and running scoped onboarding intensives that help high-growth startups confidently adopt Render's platform.
As the first FDE in Render's Field Engineering organization, you will define the playbook for this function, prove the model, and shape how it scales across the company. You'll work hands-on with customer engineering teams on architecture reviews, migration planning, and technical delivery. You'll lead the database side of engagements, including Postgres architecture, performance tuning, and complex data migrations from Heroku, AWS, and other cloud providers. You'll drive activation and expansion in strategic accounts by converting credit grants into durable production adoption, surfacing expansion signals, and partnering with account teams to convert technical wins into revenue.
You'll own the ongoing technical relationship for your accounts through proactive architecture and health reviews, collaborative roadmap sessions, incident follow-up and RCA, and serving as the escalation point for hard technical problems. You'll build the FDE playbook—qualification criteria, engagement templates, success metrics, and reference architectures—that makes the program repeatable and scalable. You'll also act as a high-signal feedback channel to product and engineering, translating customer friction into prioritized product input, and partner with Account Managers and Customer Engineers to ensure smooth handoffs and durable long-term coverage.
Render is a developer-first cloud platform for AI-native, full-stack applications, trusted by over 7 million developers. The company raised $100M in Series C funding in February 2026, bringing total funding to $260M.
REQUIREMENTS:
- 8+ years in a hands-on, customer-facing engineering role (forward deployed, solutions, customer, or professional services engineering)
- Strong software engineering fundamentals; ability to write production-quality code and work hands-on inside customer codebases
- Deep experience with cloud infrastructure: containers, CI/CD, networking, autoscaling, and running real workloads in production
- Deep Postgres and database expertise: schema design, performance tuning, replication, and production data migrations
- AI fluency: daily use of AI tools and understanding of LLM application architectures
- Excellent communication skills across startup founders, enterprise platform teams, and executive-level conversations
- Self-directed and comfortable with ambiguity; able to stand up a new function without an existing playbook
- Commercial instincts: understanding how technical wins connect to expansion, renewal, and revenue
NICE-TO-HAVES:
- Migration experience from Heroku, AWS, or other clouds
- Hands-on experience shipping AI and LLM applications (RAG pipelines, agent frameworks, inference workloads)
- Prior experience as the first hire in a role or founding member of a new program
