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$220k – $260k per year
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Remote (United States)
Seniority
Middle · 4+ years exp
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Full-Time
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The unified interface for LLMs. Find the best models & prices for your prompts

About OpenRouter

OpenRouter is the unified interface for AI inference, giving developers and organizations access to hundreds of models through a single API. Our platform helps teams choose, route, evaluate, and scale model usage across providers, making it easier to build production AI applications with the right model for every use case.

As inference becomes a core operating layer for modern software companies, OpenRouter helps customers move faster, reduce complexity, and get more value from the rapidly evolving model ecosystem.

About the Role

We are looking for a Forward Deployed Engineer to join our post-sales team and help customers successfully implement, adopt, and scale OpenRouter.

This role sits at the intersection of customer success, support, customer engineering, product, and developer relations. You will work directly with our customers after the sale to help them get live quickly, integrate OpenRouter into production systems, improve their inference architecture, and expand usage across teams and applications.

You will be deeply hands-on with developers. You will debug integrations, design implementation paths, advise on model and routing strategy, identify opportunities to increase adoption, and turn customer learnings into product feedback. The ideal candidate is technical enough to earn the trust of engineering teams, commercial enough to understand customer outcomes, and proactive enough to drive customers from initial implementation to scaled production usage.

What You’ll Do

Customer Implementation

  • Lead technical onboarding for new customers after contract close, helping them move from kickoff to production usage.

  • Partner with Customer Success Managers and Account Executives to define success plans, implementation milestones, and technical adoption goals.

  • Help customers integrate OpenRouter into their applications, workflows, infrastructure, and developer environments.

  • Troubleshoot API, SDK, model selection, routing, latency, reliability, and deployment issues.

  • Create implementation guides, reference architectures, code examples, and reusable playbooks for common customer patterns.

Inference Adoption and Optimization

  • Work with customers to understand their AI use cases, application architecture, traffic patterns, and inference goals.

  • Recommend model, provider, routing, fallback, caching, and cost-optimization strategies based on customer needs.

  • Analyze usage patterns to identify opportunities to increase adoption, improve reliability, reduce cost, or expand into new workloads.

  • Help customers evaluate models and providers across quality, latency, cost, reliability, privacy, and scale requirements.

  • Drive customers from initial API usage to broader production deployment across teams and applications.

Technical and Developer Engagement

  • Build strong technical relationships with customer developers, engineering leaders, AI teams, and platform teams.

  • Run technical working sessions, integration reviews, architecture discussions, and developer enablement sessions.

  • Act as a trusted technical advisor for customers building AI-native products, agents, internal tools, and production LLM workflows.

  • Translate complex technical concepts into practical guidance for developers and business stakeholders.

  • Advocate for developer needs internally and help improve the customer implementation experience.

Cross-Functional Partnership

  • Partner closely with Customer Success to improve retention, adoption, customer health, and expansion.

  • Collaborate with Sales on technical expansion opportunities and strategic account growth.

  • Work with Product and Engineering to surface customer feedback, feature requests, integration blockers, and product gaps.

  • Contribute to internal knowledge bases, customer playbooks, onboarding materials, and best practices.

  • Help define what excellent post-sales technical engagement looks like at OpenRouter.

What We’re Looking For

  • 4+ years of experience in a technical customer-facing role such as Forward Deployed Engineer, Solutions Engineer, Solutions Architect, Technical Account Manager, Developer Advocate, or Customer Engineer.

  • Strong software engineering fundamentals and ability to read, write, and debug production-quality code.

  • Experience working with APIs, SDKs, cloud infrastructure, developer platforms, or AI/ML infrastructure.

  • Familiarity with LLMs, inference, model evaluation, prompt engineering, agents, latency/cost tradeoffs, and production AI application patterns.

  • Ability to work directly with developers and engineering leaders to diagnose problems and design practical solutions.

  • Strong customer instincts: you understand how to drive outcomes, manage ambiguity, and build trust.

  • Excellent written and verbal communication skills, especially when explaining technical topics to mixed audiences.

  • High ownership, bias for action, and comfort operating in a fast-moving startup environment.

Nice to Have

  • Experience with OpenAI-compatible APIs, model routing, evals, observability, or LLM application frameworks.

  • Prior experience in customer success, post-sales engineering, or implementation roles at an API, infrastructure, developer tools, or AI company.

  • Experience building AI agents, chat products, copilots, automation workflows, or production LLM applications.

  • Familiarity with Python, TypeScript, REST APIs, streaming APIs, and common backend application architectures.

  • Experience working with enterprise customers, startups, or technical founders.

  • Ability to create technical content such as guides, demos, example repos, migration docs, or architecture diagrams.

What Success Looks Like

In your first 30 days, you will learn OpenRouter’s product, customer base, implementation patterns, and post-sales motion. You will shadow customer calls, understand common integration paths, and begin supporting customer onboarding.

In your first 60 days, you will independently lead technical implementation workstreams, help customers resolve integration blockers, and contribute reusable technical assets for onboarding and adoption.

In your first 90 days, you will own technical success for a set of post-sales customers, drive measurable increases in production usage, identify expansion opportunities, and create a feedback loop between customers, Customer Success, Product, and Engineering.

You’ll Be a Great Fit If

  • You enjoy being close to customers and solving real-world implementation problems.

  • You are energized by helping developers ship faster and build better AI products.

  • You can go deep technically while staying focused on business outcomes.

  • You like operating across code, customer conversations, product feedback, and adoption strategy.

  • You are comfortable with ambiguity and can turn repeated customer problems into scalable systems, playbooks, and product insights.

  • You believe inference is becoming a foundational layer of software and want to help customers adopt it successfully.

If you don't think you meet all of the criteria below but still are interested in the job, please apply. Nobody checks every box, and we're looking for someone who is excited to join the team.

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