Software Engineer - Safeguard Global

Looking for a job that fits your life, anywhere in the world? 🤔

Ever fancied a role where work molds around your life, no matter where around the globe you are? Welcome to Safeguard Global ! We're all about making work fit into your world, wherever that may be.

About us:

At Safeguard Global , we're not your average company. Sure, we enable global expansion without the risk for over 1,500+ customers in nearly 190 countries, but what really makes us tick is giving you and 900+ Guardians the freedom to work in a way that suits your style, no matter the time zone in 50+ countries. 🌎

Our “ work in any way” approach means you can call your couch your office or a café halfway across the world your boardroom, all while still having room to do school runs and essential errands throughout your working day. 🤩

What we're after:

We're building software used by companies around the world to solve complex global payroll, compliance, and workforce management challenges.

As we scale, we're transforming our platform into a serverless, event-driven architecture on AWS. This is a core engineering initiative, and you'll play a key role in shaping how our systems evolve.

We're hiring multiple engineers across several teams, so depending on your strengths and interests, you could work on areas like:

• Knowledge Platform
• Client Account Management
• Integrations
• Client analytics
• Time and Attendance

All teams share a common goal: building reliable, scalable systems that power critical business operations for our customers.

This is a fully remote role, working with a distributed team.

What You'll Do

• Design and ship agentic systems end-to-end — tool calling, sub-agent orchestration, memory, durable state, and failure recovery
• Build evaluation frameworks from the ground up — golden datasets, regression harnesses, and systematic approaches to measuring whether your AI systems actually work
• Own AI features from prototype to production: observable, maintainable, cost-aware
• Work with product and domain engineers to identify where AI has real leverage — and where it doesn't
• Contribute to how we build AI across the org: patterns, tooling, and standards that others build on
• Manage the operational economics of AI systems — latency, token cost, context efficiency — as first-class engineering concerns

What Will Give You an Advantage

• Demonstrated production experience with agentic systems: tool calling, multi-step orchestration, memory management, or RAG pipelines — with evidence (shipped product, open source, or portfolio)
• You've built evaluation infrastructure, not just run evals — you know how to measure non-deterministic systems systematically
• Strong backend engineering in TypeScript/Node.js; comfortable with Pyth