Forward Deployed Engineer (Staff)

About This Opportunity

We are representing a confidential enterprise infrastructure organization in their search for a highly technical Forward Deployed Engineer at the Staff level. This is a unique position embedded directly within the core engineering organization—not a traditional services or support role. You will work alongside enterprise client teams throughout complete platform modernization engagements, from initial architecture through production rollout, while writing production code and feeding insights directly back to product development.

This role focuses on Kubernetes platform modernization, large-scale stateful workload migration, and enterprise AI infrastructure. You'll architect solutions, troubleshoot live production environments, and serve as the direct bridge between field deployments and core engineering teams.

Responsibilities

• Embed directly with enterprise client technical teams from discovery through operational stabilization, ensuring successful platform adoption
• Write production code in the field, build prototype integrations, and work shoulder-to-shoulder with client engineers debugging live networking, storage, and GPU failures
• Architect and deploy production-grade Kubernetes clusters optimized for both general-purpose compute and accelerated GPU/NPU workloads
• Lead technical migration strategies transitioning bare metal environments and legacy data stacks to cloud-native Kubernetes platforms
• Deploy, tune, and scale production AI inferencing workloads, RAG architectures, vector search, and model serving frameworks using virtualized GPU resources
• Containerize and migrate stateful systems including message brokers, distributed caches, and analytics platforms onto Kubernetes
• Synthesize field-tested code and architectural patterns into core engineering requirements, partnering with product managers to prioritize platform features
• Identify recurring migration blockers and platform gaps, rapidly building field fixes to shorten iteration cycles from months to days
• Guide clients operating multiple Kubernetes distributions and hybrid cloud environments

What We're Looking For

• 12+ years of related technical experience with distributed systems and platform engineering
• Bachelor's degree preferred (relevant experience considered in lieu of degree)
• Deep alignment with product engineering workflows and experience working closely with core software/R&D teams rather than pure IT or services organizations
• Hands-on experience operating GPU-accelerated Kubernetes infrastructure, model serving runtimes (vLLM, Triton Inference Server), and vector databases (Milvus, Qdrant)
• Proven expertise containerizing and operating high-throughput platforms: distributed caching systems (Redis, Hazelcast), messaging platforms (Apache Kafka, RabbitMQ), and analytics engines
• Technical depth deploying cloud-native data services including Apache Spark, Apache Flink, Apache Airflow, Ray, Trino, Cassandra, and Elasticsearch
• Experience across multiple enterprise Kubernetes distributions (OpenShift, EKS, GKE, AKS, or Rancher)
• Advanced skills with infrastructure-as-code tooling: Terraform, Helm, Kubernetes Operators, Cluster API, and GitOps frameworks (ArgoCD, Flux)
• Demonstrated ability to translate customer requirements and field workarounds into clean product specifications for development teams
• Track record staying deeply engaged with customer technical leadership across long-term, complex engineering projects

How We Work With You

Candidates apply directly through Get A Job.ai. Our recruiting team will conduct an initial screening to understand your background and alignment with the role requirements. Qualified candidates will then be submitted to our client for consideration. Please do not attempt to contact the client directly, as all communication is managed through our talent team to ensure a smooth process for everyone involved.

Pay

Pay via Get A Job.ai has not been specified for this position. Compensation details will be discussed during the screening process.

Equal Opportunity: Get A Job.ai is committed to inclusive hiring practices and provides equal employment opportunity to all qualified candidates regardless of race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other legally protected characteristic.