AI-Native Software Engineer

They are looking for an AI-Native Software Engineer - first and foremost a strong software engineer, but one who understands how AI is changing both the products we build and the way we build them.

This isn’t an ML research role. You’ll be building production software, APIs, data pipelines and AI-powered workflows, while working deeply with LLMs, agents and modern AI-assisted development.

You’ll be expected to think like a software engineer first: good architecture, clean abstractions, maintainable code, testing, observability and sensible trade-offs. At the same time, you’ll work directly with modern AI systems, including multi-agent workflows, LLM APIs, tool calling, MCP and evaluation infrastructure.

You’ll be a strong software engineer who has gone deep on AI and will likely have experience with several of the following:

• Strong professional software engineering experience
• Python and backend application development
• APIs, distributed systems and asynchronous architectures
• Production cloud environments, ideally AWS
• Docker, CI/CD and infrastructure as code
• LLM APIs and production AI applications
• Agentic or multi-agent systems
• Tool calling and MCP
• LangGraph, Strands or similar frameworks
• LLM evaluation, tracing and observability
• Structured outputs and prompt engineering
• AI security and guardrails

Just as importantly, you should already be an enthusiastic user of AI-assisted development tools.

You might use Claude Code, Cursor, Codex or similar tools to explore codebases, implement features, generate tests, debug issues and accelerate repetitive engineering work - while retaining the judgement to review, challenge and improve what those systems produce., The role would suit an engineer with 1-2 years experience who loves building software, is deeply curious about AI, and believes the best engineers of the next few years will be those who learn how to work exceptionally well alongside it.

We are working with a fast-growing AI startup building a platform that helps brands understand how they are represented, recommended and discovered across AI-powered search and answer engines.

As consumers increasingly use tools such as ChatGPT, Claude, Perplexity and other AI assistants to research products, compare companies and make buying decisions, brands need a new way to understand their visibility within those systems.

The platform analyses how different models respond to thousands of commercially relevant questions, identifies the brands, competitors, sources and narratives that influence those answers, and turns this into actionable commercial insight.