Customer Success Engineer
Hedra
| Company | Hedra |
| Category | Engineering |
| Location | San Francisco |
| Remote | On-site (inferred) |
| Employment | Not stated |
| Level | Not stated |
| Salary | Not stated by the employer |
| Posted | 22 Jul 2026 |
| Last verified | 4 Aug 2026 |
| Source | Employer ATS (ashby) |
Description
THE ROLE
As a Customer Success Engineer at Hedra, you'll own the technical relationship with our customers after they sign — getting developers and enterprise teams from first integration to production, and keeping them there. You're the hands-on technical partner closest to the customer's stack: debugging API calls, architecting integrations, tuning for latency and cost, and translating what customers hit in the field into product direction with our engineering team. You'll work side by side with our Account Executives, owning technical success while they own the commercial relationship.
Responsibilities
- Own the post-sales technical relationship for our API, agent, and inference customers, from onboarding and first integration through production deployment and expansion.
- Serve as the dedicated technical resource and advocate for developers and enterprise teams: debug API calls, review integration code, and guide customers to the optimal use of our models and platform.
- Architect and troubleshoot production deployments against real constraints, latency, throughput, cost per deployment, and reliability.
- Become one of the foremost technical experts on Hedra's platform, internally and for customers.
- Translate recurring customer pain points into concrete product proposals, working directly with engineering and product to ship fixes and features.
- Partner with Account Executives to drive adoption, surface expansion opportunities, and turn early pilots into scaled production usage.
- Build and maintain the runbooks, reference integrations, and docs that let customer success scale as we grow.
Qualifications
- 4+ years in a customer-facing technical role, customer success or forward-deployed engineering, solutions engineering, technical support engineering, or software engineering with direct customer exposure.
- Hands-on technical ability. You can write Python that works, read and debug an API integration, and produce working sample code. You don't need to be a full-time engineer, but you're comfortable in a customer's codebase.
- Experience with APIs, SDKs, and developer-facing products, and comfort explaining integration paths and deployment tradeoffs to technical buyers.
- A track record of getting customers to production and keeping them successful, ideally with usage-based or consumption pricing.
- Excellent communication skills and the ability to earn trust with developers and the leaders who sponsor them.
- Demonstrated curiosity about generative AI, world models, and the inference and infrastructure that make them usable.
- BS or BA in computer science, a related technical field, or equivalent hands-on experience.
Who You Are
- Self-motivated and independent: able to set ambitious (and yet accurate!) timelines and deliver on them.
- Low ego, high patience, proactive communication. Strong opinions, loosely held.
- Understand operational costs and overhead, short and long term, and how they show up in a customer's deployment economics.
- And most importantly, treat Hedra as your own and help shape the vision with us.
ABOUT HEDRA
Hedra is a research and infrastructure lab building physical world models and the inference to deploy them at scale. Backed by top investors at Index, a16z, and Abstract Ventures, we've built the foundations for full-stack visual intelligence in the next era of AI.
Today our API serves both first- and third-party models to production customers, and our agent works within a single workflow to create content from scratch, manipulate existing assets, critique its own outputs, and repurpose them on demand. We're scaling from frontier research into the infrastructure the rest of the industry will build on.
We started by commercializing action-conditioned, real-time interactive video generation. We're now extending that foundation to the broader class of physical world models that perception, robotics, and media generation all run on.
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