Founding Applied Scientist at fast-growing AI startup

Jack & Jill/External ATS; Greater London; On-site; GBP 80,000 - 100,000; Full time

Job summary

A fast-growing AI startup is seeking a Founding Applied Scientist to shape the architecture of next-generation autonomous agents. You will design and scale knowledge infrastructure, innovating in search and retrieval systems. The ideal candidate will have world-class expertise in reinforcement learning and a strong engineering foundation to manage enterprise systems. Join as a founding member and contribute to shaping the future of agentic AI technology.

Qualifications

• World-class expertise in search, retrieval, or reinforcement learning with applied research in production systems.
• Strong engineering fundamentals to build robust, enterprise-grade systems.
• Ability to thrive in high-autonomy environments.

Responsibilities

• Design and scale long‑horizon memory and knowledge infrastructure for agents.
• Develop search and retriever systems using novel techniques.
• Apply expertise to guide agentic behavior in complex tasks.

Skills

Search

Retrieval

Reinforcement Learning

Knowledge Representation

Job description

Founding Applied Scientist

Company Description

Fast-growing AI startup

Job Description

As a Founding Applied Scientist, you will architect the foundational memory, reasoning, and learning capabilities of autonomous agentic systems. You will transcend traditional ML engineering by pioneering technologies for long-horizon planning and knowledge representation. This role focuses on building enterprise-grade superintelligence by combining cutting‑edge research with world‑class engineering to define the future of agentic AI.

Location

London, UK

Why this role is remarkable

• Be a founding member, directly shaping the core architecture of next‑generation autonomous agents
• Backed by top‑tier VCs, combining early‑stage impact with funding stability
• Innovate beyond standard RAG on unsolved problems in multi‑stage retrieval and synthetic world models

What you will do

• Design and scale foundational long‑horizon memory and knowledge infrastructure for agents to reason over evolving enterprise contexts
• Develop state‑of‑the‑art search and retriever systems using novel indexing techniques and knowledge representations
• Apply deep expertise in reinforcement learning and reasoning to guide agentic behavior in complex, multi‑step tasks

The ideal candidate

• World‑class expertise in search, retrieval, or reinforcement learning with applied research experience in production systems
• Strong engineering fundamentals to build robust, enterprise‑grade systems capable of scaling to trillion‑agent interactions
• Thrives in high‑autonomy environments and is motivated to define foundational technologies for enterprise‑level agentic superintelligence