Jobs at Runware

Own the strategy, roadmap, delivery, adoption, and revenue outcomes for Runware’s Serverless and Compute products. Partner with customers, Engineering, Design, and GTM to solve deployment, scaling, reliability, cost, and workload-management challenges. Define APIs, SDKs, CLI workflows, pricing, packaging, and production experiences for serverless GPU and dedicated compute offerings. Measure activation, usage, reliability, expansion, and revenue while making infrastructure and product investment decisions.

Owns strategy, roadmap, and revenue outcomes for serverless GPU and compute products. Works with developers, ML teams, infrastructure buyers, Engineering, Design, and GTM to solve deployment, scaling, reliability, cost, and production-operations challenges. Defines APIs, SDKs, CLI workflows, pricing, packaging, and product requirements while balancing technical trade-offs, customer needs, platform investment, and commercial outcomes.

Hands-on engineering manager responsible for leading and growing a backend engineering team, ensuring predictable delivery, technical and architectural oversight, mentoring, hiring, and cross-functional alignment with Product and DevOps to build scalable, reliable systems using modern engineering practices.

Own the end-to-end network architecture for GPU data center fabrics, backbone and edge delivery, cloud and hybrid connectivity, operations, automation, capacity planning, and vendor relationships. Design high-performance Ethernet and InfiniBand networks, optimize latency and resilience, establish observability and incident practices, and lead through technical authority. The role also sets standards, mentors engineers, shapes hiring, and uses AI tooling to accelerate network design, automation, analysis, and documentation.

Own the end-to-end storage architecture for a distributed AI supercomputer, including object storage, high-throughput pod tiers, NVMe caching, replication, and model distribution. Build and benchmark systems, optimize data movement from storage to GPU memory, establish reliability and security practices, and automate pod bring-up and operations. Partner with inference, platform, hardware, vendors, and site teams while supporting capacity planning, monitoring, recovery, data residency, and storage on-call.

Own and scale Runware’s technical support function across APIs, serverless, LLM, and GPU products. Define support tiers, SLAs, coverage, escalation paths, KPIs, and automation; recruit and develop support engineers; reduce Engineering escalations; and build knowledge bases, playbooks, and runbooks. The manager will remain hands-on with complex technical investigations, incidents, and customer communication while coordinating closely with Engineering, Product, Sales, and Customer Success.

Build and optimize automated go-to-market workflows supporting customer acquisition, activation, conversion, expansion, and retention. Integrate CRM, product, account, and revenue data; automate enrichment, targeting, scoring, routing, outreach, and CRM updates; and create tools for Sales, Marketing, and Customer Success. Measure pipeline, usage conversion, expansion, revenue, and costs through structured experiments while ensuring reliability, monitoring, error handling, permissions, suppression, and deliverability.

Own Runware’s LLM inference product strategy, roadmap, model catalog, developer experience, production requirements, and commercial growth. Partner with engineering, security, sales, marketing, and customers to improve API capabilities, inference performance, reliability, pricing, adoption, and enterprise expansion. Lead discovery, technical evaluations, product delivery, customer issue resolution, and measurement of usage, retention, revenue, margin, and service quality.

The Senior Software Engineer will design and implement systems for AI integration, build scalable backend services, and mentor team members, ensuring high-quality systems that meet user needs.

Build and maintain internal and public-facing APIs and services powering the Web App and developer experience. Develop API functionality, Admin API systems, WebSocket and REST behavior, and usage and billing integrations with Stripe. Investigate production issues and security vulnerabilities, write and review tested code, make technical decisions, and collaborate across engineering, Product, and Design teams.

Lead the development of Runware's serverless platform by building core systems for AI workload management and providing technical guidance to the team.

Lead development of Runware’s AI platform, including scalable backend APIs, SDKs, developer tools, and inference orchestration systems. Design high-performance distributed architectures, optimize image and video model integrations, improve reliability and observability, shape technical direction, and mentor engineers. Collaborate across platform, infrastructure, and product teams to deliver robust developer experiences and maintainable systems.

Experiment with generative image and video models, build advanced ComfyUI workflows and automated pipelines, and create high-quality demos, examples, guides, and social content. Translate technical experimentation into engaging developer- and creator-facing material, rapidly evaluate new model releases, and collaborate with Growth, Product, and Engineering on launches and use cases.

Lead end-to-end ML initiatives: integrate and fine-tune models, optimize GPU inference for latency and throughput, build evaluation and monitoring tooling, collaborate on scalable serving systems, and mentor engineers.

The Staff DevOps Engineer will enhance and manage infrastructure for AI inference, focusing on speed, resilience, and automation across GPU fleets and production systems.

Ensure reliability, performance, and resilience of Runware's distributed, GPU-backed production platform. Define SLIs/SLOs and observability, investigate incidents across services, databases, networking and queues, automate remediation and deployment safety, participate in on-call rotations, conduct RCA and implement long-term fixes, and collaborate on capacity planning and scaling.