Principal Engineer — Cloud Data Plane & Traffic Processing

Concentric AI
Bengaluru, Karnataka

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Job details

Full-time
8 days ago

Qualifications

CI/CD
Cloud infrastructure
Azure
Rust (programming language)
Go
Law
Kubernetes
Load balancing
Test automation
Google Cloud Platform
Java
Master's degree
Microservices
AWS
C++
C
SSL
Continuous integration
APIs
Linux
AI
gRPC
Python
Debugging
Intune

Full job description

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.

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We are looking for a hands-on Principal Engineer to own the architecture, design, and implementation of this data plane end to end.

You have shipped and operated an inline, multi-tenant, customer-traffic data plane at one of the following (or equivalent):

Cloudflare (edge / Workers / Gateway), Fastly, Akamai
Zscaler (ZIA / ZPA data plane, ZEN / PoP teams)
Netskope (NewEdge / SWG / inline steering — not Intune, notification, marketing, or config teams)
Palo Alto Networks (Prisma Access data plane)
Cato Networks, Menlo Security, Skyhigh, iBoss, Versa, Aryaka, Fortinet FortiSASE
Hyperscaler edge / gateway teams: AWS (CloudFront, API Gateway, App Mesh), Azure Front Door / App Gateway, Google Cloud (Cloud CDN, Traffic Director)
Large-scale API gateway or service mesh platform teams at Stripe, Uber, Netflix, LinkedIn, Datadog, or similar

What You'll 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.

Notice: Concentric AI never asks for money nor paid certifications during the interview process; such behavior is a known scam of which we’ve been made aware.

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Apply Now

You have shipped and operated an inline, multi-tenant, customer-traffic data plane at one of the following (or equivalent):

What You'll Do:

Required Qualifications:

Preferred Qualifications:

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