Forward Deployed Engineer

Responsibilities:

• Own client deployments end-to-end: install, configure, upgrade, and migrate the product inside customer environments (cloud, hybrid, or on-prem), including non-standard or constrained setups (air-gapped, private VPC, restricted egress).
• Be the first and primary responder on client-side issues: triage, debug, and resolve problems in the client's deployment directly. You decide what's a config fix, what's an infra fix, and what genuinely needs to go back to product engineering, and you make that call correctly.
• Diagnose and resolve network-layer issues on-site and remotely: DNS resolution failures, TLS/certificate handshake errors, firewall and proxy misconfigurations, load-balancer and ingress routing problems, VPN/VPC peering breaks, and latency or packet-loss issues inside a client's network topology.
• Handle client technical queries directly: when a client's engineer has a question or an escalation, you're the point of contact with no ticket-and-wait relay through Customer Success.
• Apply DevOps/SRE judgment to someone else's infrastructure: read unfamiliar Kubernetes clusters, networking setups, and database configurations quickly enough to diagnose environment-specific failures under time pressure.
• Partner with Presales pre-sale: join technical scoping calls for prospective clients, flag deployment and network-connectivity risks early, and shape what "supported environment" means for a given deal.
• Turn one-off fixes into repeatable playbooks: every deployment you run manually once, including network troubleshooting steps, should become a runbook, a script, or infra-as-code the next FDE (or you, in six months) doesn't have to redo from scratch.
• Build in observability by default: every client deployment ships with the monitoring and alerting needed to catch problems, including network-level ones before the client does.
• Close the loop with product engineering: recurring client-side pain feeds back as a concrete bug report, a platform request, or a proposed fix, not just a Slack message that evaporates.
• Use AI coding tools as a force multiplier: lean on AI assistants to speed up debugging and scripting inside unfamiliar client environments, while knowing exactly when to double-check output before it touches a client's production system.

Requirements:

• 4-5+ years in DevOps, SRE, or backend/infra engineering, with real ownership of production systems, not just tickets closed.
• Hands-on experience deploying software *into customer/client environments* on-prem, hybrid, or private cloud, not only internal infra you fully control.
• Strong with containers and orchestration (Docker, Kubernetes), CI/CD pipelines, and infra-as-code (Terraform, Ansible, or equivalent).
• Solid grounding in databases (Postgres, MongoDB, Cassandra, Redis), messaging (Kafka, SQS), and core networking.
• Strong networking fundamentals: TCP/IP, DNS, HTTP/TLS, routing, NAT, subnetting/CIDR, load balancing, and how these interact inside Kubernetes (Services, Ingress, CNI plugins, and network policies).
• Practical network troubleshooting skills: comfortable with tools like to isolate whether an issue is DNS, TLS, firewall, proxy, or application-layer and to explain the finding clearly to a client's network team.
• Deep Kubernetes operational knowledge: comfortable administering clusters you didn't build, reading Deployments, StatefulSets, Services, Ingress/Gateway resources, ConfigMaps/Secrets, RBAC, and debugging with `kubectl describe`/`logs`/`exec`, CrashLoopBackOff states, resource limits, and CNI/network-policy issues under time pressure.
• Working fluency in AWS and/or GCP: core compute, networking, and IAM services (VPC/VPN/PrivateLink or VPC peering/Cloud NAT, security groups/firewall rules, EKS/GKE, IAM roles and policies) well enough to deploy into and troubleshoot a client's own cloud account, not just your own.
• Observability tooling experience (logging, metrics, tracing, alerting) with a track record of using it to actually resolve client-facing incidents.
• Comfortable and confident handling client technical queries and escalations directly; no need for everything to be pre-translated by Customer Success.
• Calm, structured, and decisive under pressure during live client deployments and incidents.
• Genuinely collaborative across presales, customer success, and core engineering; this role only works if you can operate in all three worlds.