Quick overview
Job description
I'm working with a leading private equity firm building a new AI engineering team to deploy AI directly into businesses across its portfolio.
This is a genuinely hands-on role where you'll work with portfolio company executives and technical teams to identify high-value opportunities for AI, then scope, prototype and build the solutions yourself.
One project might involve building agentic workflows to automate complex business processes, while the next could focus on an entirely different AI challenge within another business. You'll gain exposure to multiple industries, business models and technical problems, with the opportunity to see your work deliver tangible commercial impact.
This isn't an advisory role. You'll be building and deploying AI solutions yourself.
What you'll be doing:
- Turning ambiguous business problems into working AI products, prototypes and POCs.
- Building with LLMs, RAG, agentic systems, tool use and modern AI frameworks.
- Working directly with senior executives and technical teams to identify and prioritise high-value AI opportunities.
- Developing evaluation frameworks to measure performance, reliability and business impact.
- Taking successful solutions through productionisation, handover and scale.
- Working closely with one or two portfolio businesses at a time, with engagements potentially lasting 6-12 months.
What they're looking for:
They're open-minded on background, but the sweet spot is around 4-8 years' experience in a
You could come from:
- A Forward Deployed Engineering or Applied AI environment.
- An AI-focused consultancy.
- A strong product engineering environment where you've combined hands-on AI development with commercial or client-facing exposure.
Technically, experience across areas such as the following would be valuable:
- Python and SQL.
- LLMs and Generative AI.
- RAG, embeddings and vector search.
- Agentic AI, tool use and multi-step workflows.
- AI evaluation and observability.
- APIs and backend engineering.
- Building and deploying production-quality software.
You don't need to tick every box. More important is that you're a strong engineer who can build quickly, navigate ambiguity and work confidently with senior stakeholders.
If you're an AI Engineer or Forward Deployed Engineer who enjoys building from scratch, solving complex commercial problems and seeing your work deployed in real businesses, I'd be keen to speak.
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