About us
At Gigawatt Industries, we’re not just installing EV chargers, we’re helping build the future of transport. As one of the UK’s fastest-growing EV infrastructure specialists, we deliver large-scale commercial and industrial charging projects for some of the country’s biggest organisations. Demand is growing rapidly, so we’re expanding our teams and looking for talented, driven people who want to be part of something exciting.
The role
Gigawatt runs a growing fleet of automations and AI agents that support internal operations: quoting, documentation, lead generation, handovers, and reporting. This role owns that layer. It finds where AI genuinely helps inside the business, designs it, then builds it. Mostly deterministic scripts and managed agents, with frontier API calls where they earn their cost.
Apply with a GitHub link and one well-documented AI project that’s deployed and in use, we care more about the one thing that runs than ten demos.
Key responsibilities
- Build agents that keep internal trackers up to date as work moves through the pipeline.
- Build workflows that turn meeting notes into tasks and draft documents from operational data.
- Build chat-facing tools that chase down what’s missing before a deadline.
- Build research and data pipelines that support other teams.
Essential
- Builds and runs AI agents and automations end to end, including scheduling, data entry, research, and document drafting. Owns them in production, not prototypes: deployment, error reporting, the 2am failure.
- Strong backend/scripting language and integration chops (APIs, webhooks, messaging platforms, internal systems), plus retries, dedupe, and idempotency, things that hold up when real work depends on them.
- Evals and monitoring. Proves a workflow works before it ships (dry-run against real data, not just green tests) and catches it when it drifts.
- Owns cost, latency, and reliability: model selection, caching, batching, fallbacks. Knows when a deterministic script beats an agent.
- Can run a room of non-engineers, doing discovery with operational and business stakeholders.
Desirable
- Notion (a lot of our stack sits on it).
- Agent frameworks like OpenClaw or Hermes.
- Python.
- Self-hosting chops: Docker, reverse proxies, object storage.
- n8n/Make-type automation.
- MCP.
- Local/open-weight LLM setup for private docs.
- Any exposure to construction, utilities or field-ops businesses.