Applied AI Engineer - fast-tracker, small VC equity leader

AI Engineer - Forward Deployed London - hybrid (2-3 days in office) £115-175k plus performance bonus

Make sure to apply with all the requested information, as laid out in the job overview below.
A leading growth equity firm investing in enterprise technology businesses across the UK and Europe is hiring an elite Forward Deployed AI Engineer - an influential, hands-on individual contributor who will play a foundational role in shaping how AI is used across the investment lifecycle.

Were interested in talking to a high achieving, high energy, fast tracker with around 3-5 years in a top tier environment, post-University. An AI native with an engineering background and mindset.

Importantly, you will have worked in high-context environments where engineers work directly with end users to deliver real-world AI systems - define the technical stack, set the roadmap, and own the end-to-end delivery of internal AI systems.

As the sole AI Engineer, you will have responsibility for E2E delivery (yes, including all development + implementation), and the chance to build from a blank slate, shaping the firms AI capability, including sourcing, research, diligence, and workflows.

This is a highly autonomous role with significant responsibility and the freedom to experiment, iterate, and drive impact quickly. Youll move fluidly between rapid prototyping and production rigor, applying technical creativity to commercial decision-making.

More on the role: Build internal AI-powered tools, systems and agents to streamline sourcing, research, diligence, and portfolio monitoring
Design and deploy end-to-end LLM applications including research copilots, RAG systems, workflow automation, data enrichment, and deal intelligence tooling
Ingest, clean, and analyse external datasets through scripts, pipelines, and lightweight ML components
Integrate third-party APIs, datasets, scraping frameworks, and internal systems such as CRM and deal flow platforms
Rapidly prototype MVPs, validate value with the investment team, and harden the most impactful tools into reliable internal products
Build simple internal interfaces using FastAPI, Streamlit, or Next.js to enable intuitive adoption
Implement evaluation, observability, and governance to ensure accuracy, reliability, security, and responsible use of AI systems
Guide and coach the investment team on the latest tools, processes

Skills and Experience: circa 3-5 years in software engineering, applied AI engineering, ML engineering, or forward deployed roles
Strong Python
Experience building and deploying LLM applications (OpenAI, Anthropic, Gemini, etc.)
Deep familiarity with RAG methodologies, embeddings, and vector databases (Pinecone, Weaviate, pgvector)
Robust API integration experience, including working with third-party datasets, web APIs, or scrapers
A product mindset, enjoys crafting scrappy prototypes that evolve into polished tools
Strong communication skills and the ability to collaborate directly with non-technical business users
Exposure to finance, enterprise data tooling, or B2B SaaS analytics is a bonus
The AI Engineer will thrive in real-world environs where delivery is all - settings where you work directly with end users, navigate ambiguous or evolving requirements, and need to understand the commercial context as deeply as the technical one.

It is envisaged that over time the role could evolve to include an element of trusted advisor / thought partner (i.e. for portfolio company / prospective investee company CEOs etc). xwzovoh Given the elite calibre and potential of the person were after, there is a clear leadership path within the organisation.