Customer Success Engineer
Listed on 2026-06-06
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IT/Tech
Data Engineer, AI Engineer, Technical Support, Systems Engineer
We’re a global tech company, just not the kind you’re picturing. Our team of nearly a thousand people wakes up every day to make our product and our customers’ lives better. At Safety Culture, you’ll hear “yes, let’s give it a shot” more often than “that’s not how we do things here.”
People join because we’re building tools that make work better for the 3 billion people who keep the world moving: factory floor operators, baggage handlers, truck drivers, servers, store assistants. The ones who make things happen. We’ve got the scale and innovation you’d expect from big tech. The difference? No endless layers of sign‑off. No corporate theatre. Just smart, experienced people solving real problems fast.
The scale is big, but the ownership is personal. Every full‑time team member gets equity: real skin in the game. When we grow, you do too. This next chapter is about scaling with intelligence, not just size, fueled by operational maturity, a clear vision, and a strong focus on AI.
Role PurposeThis Customer Success Engineer role exists to unlock technical value for Safety Culture’s Enterprise customers, designing and implementing solutions that ensure customers integrate deeply with the platform and realise measurable operational outcomes, while bridging the gap between Go‑to‑Market (GTM) teams and Product, Design & Engineering (PDE).
Key Responsibilities- Own technical solution design for Enterprise customers: from scoping integrations and data workflows through to working implementations that enable full platform value.
- Partner with Customer Success Managers (CSMs) to build implementation plans that accelerate time‑to‑value for managed accounts.
- Work alongside Account Executives (AEs) during pre‑sales to communicate technical platform capabilities (APIs, security architecture, and cloud integrations) and resolve technical blockers in the sales cycle.
- Act as a technical bridge between GTM and PDE, capturing and routing customer integration feedback that shapes the product roadmap.
- Build lightweight technical solutions (scripts, automations) that extend platform capability for specific customer use cases.
- Advise customers on integration architecture: how to connect Safety Culture to their existing systems effectively and sustainably.
- Partner with the API and Integrations Engineering team to resolve complex customer requirements and advocate for platform improvements that benefit the broader customer base.
- Proven ability to design and implement data solutions: writing SQL queries, modelling relational databases, and translating raw data into business‑relevant insights.
- Comfortable building across scripting or programming languages (e.g. Python, JavaScript, Ruby, Golang) to automate workflows or extend platform capabilities for specific customer use cases.
- Able to navigate a wide variety of enterprise system architectures, data models, and integration patterns.
- Confident reading API documentation and building or troubleshooting API integrations in enterprise environments.
- Background spanning software development and data analytics; comfortable moving between building solutions and communicating data‑driven insights to non‑technical stakeholders.
- Translates fluently between technical and non‑technical audiences: equally credible in an engineering deep‑dive and a customer‑facing session with business stakeholders.
- Stays organised across a high‑volume, concurrent workload; switches context quickly without losing quality or missing detail.
- Customer‑first problem solver: listens to understand the real need before proposing a solution, and brings options rather than just problems.
- Self‑directed and comfortable with ambiguity; identifies what needs to be built or fixed without waiting for a detailed brief.
- Team‑first mindset: invests in the success of CSMs, AEs, and engineering partners, not just their own outcomes.
- Uses AI tools to accelerate integration work, drafting technical specs and documentation, analysing customer data to surface insights, and building automations faster.
- Applies AI coding assistants fluently in day‑to‑day work; evaluates…
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