• Own CRM data integrity, including custom objects and integrations, pipeline hygiene, attribution and reporting accuracy, and integration with marketing, product, and analytics systems • Develop internal GTM tooling using code and automation, including APIs, webhooks, and event-driven integrations, Python and scripting for data processing and automation, and automation that reduces manual work for sales and marketing teams • Integrate product usage and behavioral data into GTM systems to improve customer delight and retention, trigger contextual outreach and follow-ups, and support expansion and upsell workflows • Build dashboards and analytics that provide funnel visibility from lead to revenue, conversion, velocity, and drop-off insights, and feedback loops for continuous GTM optimization • Partner closely with sales, marketing, and product to translate GTM strategy into automated systems, rapidly test and iterate on GTM experiments, and scale what works while eliminating manual or low-leverage processes

• Take ownership of an ML deployment system spanning multiple production environments and continue to research efficient and effective strategies. • Improve, expand, and streamline our existing deployment pipelines to support faster deployments and automated model retraining. • Collaborate with Data Scientists to understand model requirements and provide guidance to ensure seamless integration with production environments. • Develop automations that empower data scientists to self-serve, remove manual steps from our processes, and streamline their training workflows. • Build and maintain production-level inference environments, including low-latency real-time APIs and batch predictions, and monitor these environments to ensure uptime, resiliency, and latency SLAs are met. • Work with modern CI/CD tools to deploy ML/AI models at scale in a production setting. • Drive the deployment and optimization of custom AI and LLM models, supporting data scientists and AI engineers in fine-tuning, evaluating, and serving large language models for real-world use cases. • Contribute to the infrastructure, pipelines, and monitoring needed for generative AI systems, including vector databases, prompt orchestration frameworks, and scalable inference services. • Enjoy a great company culture rich in collaboration, teamwork, no politics, learning, and frequent wins.

• Integral member of the team defining and building Muon’s satellite bus platform • Translate concepts and requirements into design and working implementations, supporting through to on-orbit operations • Design, bring up, and support the embedded software environment that runs in our satellite flight systems and peripherals using ARM Cortex-M CPUs. • Participate in evaluating and selecting technologies for our software foundation • Write application, platform, and driver functionality in our flight software environment and teach others how to use it • Integrate compute and peripheral subsystems in both software and hardware • Collaborate with hardware team members on the design and bring up of Muon hardware • Collaborate with software team members to set flight software architecture, select infrastructure and tools, and communicate with cloud backends. • Participate in developing software and hardware-in-the-loop test strategies

**The Role** **This is both an engineering and leadership role. On the engineering side, be prepared to get your hands dirty on everything from low-level infrastructure, performance, and security to user-facing product features. You will also be a primary steward of longer-term architectural decisions and projects. In addition to being a full-stack engineer (in every sense of the word), you will work very closely with the CTO to help determine product and engineering strategy and priorities, mentor other engineers, and grow the team. We are looking for people in New York, the East Coast (USA), or Mexico City. ** That means: -Working directly with customers’ logistics, IT, and operations teams to deeply understand their needs and pains (customer meetings often take place in both Spanish and English, with live translation as needed) -Lots of autonomy, using customers’ needs to guide your decision-making -Making pragmatic architecture decisions -Taking end-to-end ownership of large, business-critical projects -Working with cutting-edge AI tools in our product and your own development workflow