Forward Deployed Engineer

Job Description

Job Description

About Us

We are on a mission to bridge the gap between enterprise business knowledge and data, democratizing data discovery and curation to prepare organizations for the era of generative AI. Today's data tools are overly complex, poorly integrated, and siloed, forcing AI Practitioners and data scientists alike to spend more time wrestling with tools, relying on tribal knowledge, and navigating data lakes rather than doing meaningful data science work. The current landscape of data tools and processes is heavily manual and needs to catch up with the vast amount of data generated daily. With the advent of Gen AI and multi-modality, this challenge has only grown more complex and broken.

Backed by top VC funds, we are committed to making enterprise data AI-ready faster, more reliably, and with a stronger foundation of factual semantic knowledge. This leads to more accurate models, superior outcomes, and better business results. Our team of seasoned data infrastructure and machine learning experts (from LinkedIn, Visa, Truera, Hive, and Branch) has spent the past two decades building bespoke systems to solve these very challenges.

Join our growing team of ML research and data infrastructure experts. We're committed to empowering AI and data scientists to seamlessly integrate semantic learning with generative AI. Be part of our journey to shape the future of enterprise AI.

About the Job

We’re looking for a Forward-Deployed Engineer to join our founding team and bring our AI-native data infrastructure to life in real-world environments. This is a hybrid role blending infrastructure, product, and delivery—you’ll work across systems, tools, and teams to bring new deployments from concept to scale. Think of it as a "jack-of-all-systems" role : one foot in Kubernetes and Ray clusters, the other in semantic pipelines and user-facing use cases. You’ll be a first responder, architect, and operator—deploying zaimler’s semantic infrastructure into dynamic enterprise settings, collaborating closely with ML and infra engineers, and making sure customers get value from day one.

This role prefers candidates in or aligned to the Eastern Time Zone (EST) & will require travel onsite to customer locations.

What You Will Be Doing

• Build, deploy, and scale zaimler’s platform in diverse customer environments (Kubernetes-native, often hybrid cloud)
• Own the infrastructure stack : provisioning, scaling, monitoring, and incident handling for data / ML pipelines.
• Stand up and optimize distributed compute systems using Ray, Kubernetes, and supporting cloud services.
• Bridge ML and infra—help ML engineers productionize knowledge extraction, entity linking, and retrieval pipelines
• Write Terraform, Helm charts, Dockerfiles, and bash scripts that others rely on
• Contribute to internal tooling, automation, and observability to make zaimler repeatable and scalable.
• Interface directly with early customers to understand their environment, workflows, and edge cases.

Prior Experience

Nice to Haves

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.