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About the Role We are building the inline cloud data plane that powers a next-generation AI security platform. This service terminates TLS, inspects and processes enterprise AI traffic in real time, and applies policy, classification, orchestration, auditing, and analytics at millisecond latencies under production SaaS load across multiple global regions. We are looking for a hands-on Principal Engineer to own the architecture, design, and implementation of this data plane end to end. What Youll Do Architect and build the inline cloud data plane that processes enterprise AI traffic in real time. Own the request path end to end: TLS termination, HTTP/2 and HTTP/3 handling, policy evaluation, classification hooks, upstream routing, and response streaming. Design multi-tenant, multi-region PoP architecture with strict p50 / p95 / p99 latency budgets and availability SLOs. Design and implement request routing, service discovery, resiliency, timeout, retry, circuit-breaking, and backpressure strategies on the hot path. Optimize the platform for added latency, throughput, connection density, TLS handshakes/sec, and cost per million requests. Drive cost and operational efficiency across the data plane, including capacity planning, autoscaling behavior, infrastructure utilization, and cost per unit of traffic. Integrate the data plane with policy enforcement, classification, orchestration, auditing, analytics, and other core platform services. Define the control-plane integration model for configuration distribution, policy propagation, service discovery, tenant isolation, and safe rollout of data-plane changes. Build distributed tracing, metrics, and end-to-end observability tuned for inline request-path debugging. Architect Kubernetes-based deployments, horizontal autoscaling, rolling upgrades, and multi-region disaster recovery for the data plane. Drive technical decisions on proxy technology selection (Envoy vs. custom vs. hybrid), extension model (filters, WASM, native), and control-plane integration. Mentor engineers and set the engineering bar for inline-service development, incident response, and operational excellence. Required Qualifications 10+ years of software engineering experience, with at least 5 years building or operating an inline, customer-traffic, low-latency SaaS data plane (proxy, gateway, edge, CDN, SASE/SWG, or equivalent). Production experience with a programmable L7 proxy Envoy, Nginx/OpenResty, HAProxy, Squid, or a comparable in-house proxy including writing filters, modules, or extensions. Deep hands-on expertise with HTTP/1.1, HTTP/2, HTTP/3 (QUIC), gRPC, WebSockets, TLS (termination, MITM/SSL-inspection, SNI, session resumption, cert management at scale), and streaming architectures. Proven track record of hitting hard SLOs on a live data plane: peak RPS, p99 added latency, TLS handshakes/sec, concurrent connections you can quote your numbers. Strong expertise in multi-tenant, multi-region service design, including PoP architecture, global load balancing, and failover. Deep understanding of Kubernetes and cloud-native application design as it applies to inline, stateful / long-lived-connection workloads. Strong systems-programming skills in Go (preferred), Rust, C++, or Java. Experience with observability platforms OpenTelemetry, Prometheus, Grafana, or Datadog for high-cardinality, request-path observability. Excellent architectural, debugging, and performance-optimization skills under production load. Preferred Qualifications Experience building or extending Envoy (filters, xDS control plane), API gateways (Kong, Apigee, Tyk), service mesh (Istio, Linkerd, Consul Connect), or edge/CDN platforms. Production experience with SWG, SASE, CASB, ZTNA, or forward/reverse proxy products. Experience with AI/LLM traffic patterns (streaming responses, long-lived SSE/WebSocket connections, token-level inspection). Experience designing systems supporting high-throughput traffic processing, horizontal autoscaling under sudden load, graceful degradation, and per-tenant fault isolation. .
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.