דרושים Forward Deployment Engineer - Client Solutions בתל אביב

Forward Deployment Engineer - Client Solutions

About the Team

Airis Labs works with clients who need to extract meaningful intelligence from everyday footage. Our Forward Deployment Engineering team bridges the gap between raw data and real operational insights.

We combine DevOps, product engineering and hands-on development to turn platform capabilities into field-ready systems. The team works directly with clients, uncovers where value is locked in their data, and builds solutions that bring that value to the surface. We operate as a technical partner embedded in real workflows, shaping the path from prototype to deployment.

About the Role

Forward Deployment Engineers own the delivery of production-grade systems that enable clients to unlock intelligence from their data. You will work closely with users and technical teams in their environment, understand operational constraints, and design infrastructure, services, and data flows that integrate cleanly with their existing systems. You will scope, build, deploy, and support solutions built on Linux, Kubernetes, Helm, Python, and Terraform.

Success in this role means bringing structure to ambiguity, moving quickly while maintaining quality, and ensuring that what you deliver provides measurable value. You will identify recurring patterns, improve deployment practices, and contribute field insights that influence product direction.

In This Role You Will

• Own delivery across multiple deployments from initial discovery through stable production
• Architect and operate cloud or on-prem environments using Linux, Kubernetes, Helm, Terraform, and Python
• Embed with client teams to understand workflows and help them unlock intelligence from their data
• Work closely with Airis Labs business and R&D teams to align technical delivery with client goals and priorities
• Partner with R&D teams to bring emerging capabilities into real deployments and provide feedback from field use
• Scope work, sequence delivery, and drive momentum across teams
• Build automation, pipelines, and observability to ensure reliability and repeatable deployments
• Write production code for services, data processing, or tooling when needed
• Convert repeated patterns into reusable deployment modules or playbooks
• Share insights from client environments that influence product and engineering decisions
• Maintain alignment across internal and external groups through clear communication and consistent execution

You Might Thrive Here If You

• Bring 3 to 6 years of DevOps, Engineering, Platform or technical deployment experience
• Are fluent in Linux operations, distributed systems, and debugging real world infrastructure on site
• Have deep experience with Kubernetes and Helm in production contexts
• Have experience with writing production Python for services, automation, or data processing
• Have experience with working on air-gapped systems
• Use Terraform or similar IaC tools for managing reproducible environments
• Communicate clearly with R&D teams, product teams, and client stakeholders
• Simplify complexity and make sound decisions when timelines are tight
• Have delivered complex systems where requirements shift quickly or are initially unclear
• Enjoy working on site and collaborating directly with users

Why this role? Why now

• A growing field where forward deployment work is becoming essential in how companies adopt real AI systems
• Hands-on experience working directly in client’s environments and shaping real-world outcomes
• A chance to create meaningful impact by helping organizations unlock intelligence from their data
• A unique blend of product engineering, DevOps, development, and customer-facing problem solving
• Exposure to challenges and responsibilities that go far beyond typical development roles
• An opportunity to drive clarity, influence decisions, and own end-to-end delivery in high-value environments

Additional Expectations

• On-site work is required based on client needs
• Some travel may be needed depending on deployment scope
• Must be comfortable working in secure or air-gapped environments with limited external connectivity