Forward Deployed Engineer

In your first 3 months, you will have:

Taken full ownership of at least one customer account and delivered a clear, measurable improvement in real-world customer value.

Built strong context on customer constraints and operational realities and used it to make sound trade-offs across product, systems, and delivery.

Earned trust through autonomy, responsiveness, and high-quality execution—becoming the person teams rely on to move deployments forward.

In your first year, you will be:

Independently owning multiple deployments or a strategic account end-to-end, consistently compressing adoption cycles and driving measurable outcomes.

Creating repeatable deployment patterns that materially reduce delivery friction and improve speed-to-value across customers and partners.

Feeding a steady stream of product improvements back into Engineering, helping evolve the platform based on real-world constraints and learnings.

5+ years building and operating production software or systems, ideally in customer-facing or delivery-oriented roles.

Experience operating in complex environments across infrastructure, networking, security, data systems, and/or production AI (e.g., Linux, Docker/Kubernetes, REST/gRPC APIs, and modern observability tooling).

Strong engineering craft: clean implementations, thoughtful designs, operational clarity, and strong documentation (e.g., Python and/or Go, shell scripting, and reliable integration practices).

Comfort working in ambiguity and making sound trade-offs, especially when timelines and constraints are real.

Clear communicator and strong collaborator across technical and non-technical stakeholders.

Ownership mindset: outcomes over tasks; you naturally take responsibility for delivery, adoption, and customer value.

Delivering complex deployments end-to-end and turning one-off wins into repeatable patterns (e.g., deployment playbooks, runbooks, and reusable configuration templates).

Hands-on experience with edge or hybrid systems across hardware, networking, connectivity, and containerized software environments (e.g., VPNs, TLS, firewalls, LTE/5G/Wi-Fi, and Kubernetes deployments).

Deep comfort diagnosing and solving cross-stack issues in production environments (e.g., logs/metrics/traces, packet capture, network debugging, and performance profiling).

Production experience applying modern AI systems (LLMs, agents, inference) in real customer workflows under real constraints (latency, bandwidth, reliability, and security).

Experience embedding with customer and partner engineering teams to align multi-party delivery toward measurable outcomes.

At Edgescale AI, we’re deploying AI in the real world—helping customers apply this technology to unlock transformative productivity gains. Our work sits at the intersection of infrastructure, security, networking, and AI, where reliability and performance are non-negotiable and where solutions demand deep, distributed systems thinking.

We’re intensely AI-native. We build with AI, we ship AI, and we use it every day to accelerate how we design, test, deploy, and operate complex systems. If you want to help pave the application of AI in the real world, at global scale, we want to hear from you.

Edgescale AI is building an inclusive, merit-based organization. We are an equal opportunity employer and do not discriminate on any legally protected status. We value diversity, inclusion, and a shared passion for creating real-world impact.