Senior Forward-Deployed AI Engineer, Customer Eng

Jobs Paloaltonetworks; England; On-site; GBP 110,000 - 155,000; Full time

Job summary

Palo Alto Networks is seeking a hands-on Forward Deployed Engineer for Prisma AIRS. You will embed with customer teams, write production code, design low-latency topologies, and build custom plugins to ship secure enterprise AI workloads.

You will bridge customer environments and core engineering, extending the platform edge while contributing code back to the core engine. Strong cloud-native and security credentials are required.

Qualifications

• Education in CS/AI or related field or substantial practical experience.
• Proven ability to develop, debug, and integrate enterprise APIs (REST, gRPC, WebSockets).
• Experience with LLM orchestration, prompt security, and vector databases preferred.
• Cloud-native infra experience across AWS/GCP/Azure and IaC tooling.
• Security-first mindset with zero-trust networking and secure API integration.
• Testing with PyTest/unittest and distributed system validation.

Responsibilities

• Write production-grade code to integrate Prisma AIRS with microservices and multi-cloud architectures.
• Build middleware/plugins for identity-aware policies and telemetry pipelines.
• Develop deployment modules with Terraform, Helm, and Kubernetes.
• Optimize high-throughput, low-latency data paths and streaming workloads.
• Lead architectural reviews for zero-trust deployments with senior engineers.
• Deploy across multi-LLM providers and on-prem/off-cloud setups.
• Diagnose distributed systems bottlenecks and analyze traces.
• Contribute back to core product repositories.

Skills

Python

Go

TypeScript

C++

APIs (REST/gRPC/WebSockets)

Education

Bachelor's or Master's in CS/AI or equivalent experience

7+ years professional software engineering

Tools

Envoy

Kong

Terraform

Kubernetes

Docker

Job description

Palo Alto Networks is seeking a hands-on Forward Deployed Engineer for Prisma AIRS. You will embed with customer teams, write production code, design low-latency topologies, and build custom plugins to ship secure enterprise AI workloads.

You will bridge customer environments and core engineering, extending the platform edge while contributing code back to the core engine. Strong cloud-native and security credentials are required.