Principal Software Engineer

Help us build the "System of Action" that supercharges global manufacturing teams. QAD is entering a high-velocity era to architect the world’s first AI-native, agentic ERP. We are moving beyond legacy "systems of record" to build an autonomous platform where humans and AI work as a tag team to redefine how factories operate. Join us at this pivotal moment to build our next generation platform, lead the next generation of the Adaptive Enterprise and turn global speed into strategy.

Ignite Your Future

As an Engineering Manager at QAD, you will lead an agile engineering team responsible for designing, building, and delivering high‑quality software. You will combine hands‑on technical understanding with people leadership, helping engineers do their best work while delivering meaningful business outcomes.

Active use of AI-native development workflows — Cursor, Claude Code, and CodeRabbit or equivalent — is a baseline requirement, not a nice-to-have. We treat AI augmentation as the standard engineering operating model. Leaders are expected to use these tools personally, set norms for their teams, and demonstrate that AI tooling raises the output of their entire squad. Candidates who view AI tools as optional or experimental are not the right fit for this organization.

The Mission: What You'll Be Building

You will guide a team building features and services across QAD’s adaptive, cloud‑native platform, contributing directly to customer‑facing capabilities and platform foundations.

Lead for the engine room of ERA — the runtime infrastructure that autonomous agents execute on.

The Mindset

- People-Centered Leader: Cares deeply about team health, growth, and inclusion.
- Execution-Oriented: Focuses on delivering value consistently and reliably.
- Technically Curious: Continuously builds technical depth to better support the team.
- Accountable Owner: Takes responsibility for commitments and outcomes.
- Collaborative: Works openly with Product, QA, and peer teams.

Responsibilities

Deliver the Orchestrator, Reasoning Engine, Agent Runtime, and Session/Memory Management systems; Own the LLM Gateway: model routing, cost governance, latency SLOs, prompt versioning, and model fallback; Ensure production reliability: agent sandboxing, execution audit trails, timeout handling, and retry logic; Manage a squad of 5 engineers, including 1 Principal Engineer

Requirements

6+ years in backend or AI/ML engineering with at least 2 years managing a squad; Experience operating production LLM systems — real SLOs, real failure modes, real post-mortems; Deep understanding of agentic frameworks: orchestration patterns, tool use, and multi-step reasoning; MCP (Model Context Protocol) implementation experience; Prompt versioning, eval pipeline design, and agent behavior testing; Responsible AI guardrails and agent safety architecture