AI Engineering Lead

Shift is hiring an AI Engineering Lead - a Shiftmaker who will own the intelligence layer of our product.

ABOUT SHIFT

Shift is an AI-native consultancy dedicated to helping organisations navigate the complexities and opportunities brought by AI innovation. We blend the capabilities of artificial intelligence with the critical value of human judgment, accountability, and common sense. By combining experienced transformational leaders with our AI-powered platform, we support businesses in achieving impactful, people-centred work.

THE ROLE

As AI Engineering Lead, you'll lead, develop, and advise on the product. You'll own the intelligence layer of the platform, designing, building, and continuously improving the agent pipelines, prompt architecture, and integration fabric that make it work. This isn't prompt tinkering. It's systems engineering applied to AI.

You'll act as the technical authority on the product itself, working hand-in-hand with the Product Owner. They own the what and the why, you own the how. Together you'll set the pace, the priorities, and the quality bar for what ships.

You'll have real ownership of the product and the autonomy to do the job properly. No layers, no politics, no waiting for permission to do good work. If you've been wanting to build proper AI systems at the edge of what's possible, and have the autonomy to do it your way, this is for you.

WHAT YOU'LL DO

• Own and evolve our multi-agent pipeline, improving automation rates, output quality, and reliability iteratively
• Design and implement prompt engineering patterns, chain-of-thought structures, and context management strategies across agent workflows
• Build and maintain the knowledge and retrieval layer that grounds agent behaviour in real context
• Shape how people experience working alongside the agents, keeping the handoffs seamless and the control intuitive
• Integrate the agent layer with backend services and the user-facing interface to ship coherent end-to-end experiences
• Partner with the Product Owner day-to-day, translating priorities into delivery, surfacing trade-offs, and shipping what matters
• Iterate in short cycles. Ship, measure, learn, repeat, without waiting for ceremony to tell you something isn't working
• Set the engineering standards and practices for how the product is built and maintained

WHAT YOU'LL BRING

• Demonstrable experience building production systems with leading LLM APIs, well beyond toy projects
• Strong Python skills, with a track record building robust services and working close to infrastructure
• Hands-on experience with retrieval and knowledge-grounding techniques in production or near-production contexts
• Systems thinking: you see agents as components in a larger architecture, not magic boxes
• Able to keep several threads moving in parallel, switching context without losing momentum
• Comfort with ambiguity; you can define the problem before solving it

BONUS POINTS

• Experience deploying container-based services in a cloud environment
• Familiarity with multi-tenant SaaS patterns
• Background in enterprise software or B2B SaaS
• Prior experience in a startup or product company at an early stage