z

Forward Deployed Engineer

zaimler
Full-time
On-site
New York, New York, United States
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

    • 3+ years of experience in backend or infrastructure roles (infra/platform, SRE, or devops welcome)
    • Deep familiarity with Kubernetes, Docker, Terraform, and Helm
    • Experience managing or deploying distributed compute frameworks (Ray, Dask, Spark, etc.)
    • Fluency in at least one scripting language (Python, Bash, Go preferred)
    • Strong debugging skills across the stack—from network hiccups to memory leaks
    • Experience deploying in cloud-native environments (AWS/GCP/Azure)
    • Comfortable being customer-facing and managing ambiguity in real-time
    • Strong sense of ownership and bias toward action in early-stage environments

Nice to Haves

    • Experience deploying or integrating LLMs or vector databases
    • Background in ML Ops or building/operating data infrastructure at scale
    • Familiarity with GPU optimization, multi-tenancy, or air-gapped environments
    • Prior startup or zero-to-one deployment experience
    • Familiar with Ray Serve, VLLM, or similar frameworks
    • You’ve been in a forward-deployed, solutions engineer or field engineer role before
Apply now
Share this job
Twitter Facebook Linkedin Email