Sr. Staff Software Engineer - Austin, TX

Trend Micro•Austin, TX

10h•Hybrid

About The Position

TrendAI™, the global AI security leader and enterprise business unit of Trend Micro, empowers organizations with full AI visibility and consolidated security that inspires confidence, drives innovation, and eliminates risk. At TrendAI™, we’re always seeking exceptional talent; people who want to collaborate with the best and push boundaries together. Here, your work goes beyond building a career. You will help protect what matters and play a vital role in shaping a safer, more trustworthy AI-powered future. AI Fearlessly. This is a hybrid role based out of our Austin, TX office and requires in-office presence three days a week (Tuesday, Wednesday, Thursday). TrendAI is seeking a Senior Staff Software Engineer to help build Trend Vision One™ Private Access, our Zero Trust Network Access (ZTNA) capability. Private Access lets enterprise customers reach internal applications — RDP, SSH, web — without exposing those apps to the public internet and without a traditional VPN. The Austin team works across three pieces of Private Access: a Connector on-premises next to the customer's application; a Relay in our cloud that brokers the connection between the end user's device and the Connector; and a Controller of cloud microservices that runs the policy, identity, and authorization plane. The product runs across many global cloud regions to meet customer compliance and latency needs. This is a hands-on engineering role with architectural scope. We're moving in the same direction as the rest of the industry: engineers no longer just write code; we design the systems that produce it. Concretely, we're building toward a daily loop where: Engineers work through an agent harness (Claude Code, plus its peers) layered on top of GitHub Actions, Jira, CI/CD, docs, and runtime data. Agents handle most of the inner development loop. Humans gate at the edges — architecture, end-to-end validation, the failures the agents can't resolve, and the question of what "good" actually means. Engineers design the pipeline; if the output is bad, we fix the assembly line. We're partway through this transition and the candidate we hire will help define how much further it goes. AI makes mistakes — confidently. A senior engineer's value shifts from typing code (AI does that) toward defining the right requirements, catching the plausible-but-wrong output, and bringing the context AI doesn't have. The skills that matter most: Systems thinking — catch failure modes (latency, cost, drift, silent failures) before they reach production. Operational instinct — when something looks off in production, reach for metrics, profiling, and autoscaling without waiting for an SRE. Critical review — design validation layers and catch the subtle thing that looks right but isn't. Security thinking — zero-trust is the product and the development model; reason about access control, data protection, and safe execution boundaries by default. Domain expertise — understand (or be ready to learn) our customers' environments, the problems they bring us, and the operational realities that aren't in any spec.

Requirements

7+ years of experience building production backend systems.
Equally comfortable with Kubernetes-deployed services and software that ships as a Linux VM — our stack spans both.
Strong proficiency in Go or an adjacent systems-leaning language (Rust, C++, or similar) and willingness to be polyglot in our stack (Go, Python, some C/C++).
Demonstrated experience operating software that runs in customer environments — on-prem services, marketplace images, update mechanisms — and the realities of long-tail version compatibility (customers do not upgrade on your schedule).
Hands-on production debugging with metrics, profiling, and autoscaling (HPA / KEDA).
Linux internals (systemd, namespaces, networking) at a level sufficient to debug a misbehaving Connector running on a customer's host.
Networking fundamentals (TCP/IP, TLS, proxies, NAT, firewalls) — the Connector and Relay carry customer traffic directly.
Demonstrated experience using an agent harness like ours in real engineering work, and the judgment to direct, review, and validate its output.
Excellent written communication; ability to write design documents that survive review.

Nice To Haves

Prior work on a ZTNA, SASE, SSE, VPN, or other network security product.
Distributed systems experience — consistency, retries, idempotency, and reasoning about partial failures across services and regions.
Production depth in Microsoft Azure (where our cloud services run).
AWS and Oracle Cloud Infrastructure (OCI) experience is a plus — the Relay also deploys to those clouds for regions where Azure isn't available.
CI/CD and supply-chain hygiene: signed releases, SBOM, reproducible builds.
Experience designing or operating an LLM-powered system in production (RAG, agentic workflows, or otherwise).
Track record of driving architectural decisions across multiple services and lifting peers along the way.

Responsibilities

Design and implement features across the Connector, the Relay, and the Controller services that drive them.
Own one or more Controller microservices end to end (rule engine, geolocation, event workers, proxy paths, connector management).
Diagnose and resolve performance issues in production: memory pressure, CPU saturation, latency hotspots, autoscaling tuning.
Write architecture proposals and design documents; drive them through review with peers and the team's architect.
Investigate complex production support cases — the ones that require domain expertise about a customer's environment, an interop quirk, or proposing a different approach to their problem.
Contribute to the team's AI-augmented development pipeline: shape what gets autonomous, where humans gate, and what validation is non-negotiable for a security product.