Applied AI Engineer

Barlowe LLP; Greater London; On-site; GBP 80,000 - 120,000; Full time

Benefits offered by this job

Highly competitive compensation

Annual discretionary bonus

35 days annual leave

9% company pension contributions

Comprehensive healthcare and life assurance

Cycle-to-work scheme

Monthly company events

Job summary

Barlowe LLP in London is seeking a skilled engineer to develop platforms that drive high-impact research. You will work on projects that utilize modern AI technologies, transforming how teams collaborate.

Key responsibilities include building scalable systems and collaborating with various teams. The ideal candidate should have a strong software engineering background and experience with LLM-powered systems. Competitive compensation and numerous benefits are offered, including 35 days of annual leave.

Qualifications

• Experience with context engineering: retrieval strategies, prompt construction.
• Ability to work across domains with different teams.
• Contributions to open-source AI projects or conference talks.

Responsibilities

• Work across areas such as retrieval and knowledge systems.
• Own high-impact projects from initial concept to production.
• Partner with teams to identify problems and deliver scalable solutions.

Skills

Strong software engineering background with modern AI technologies

Hands-on experience with LLM-powered systems

Strong Python engineering skills

Experience with evaluation and observability for AI systems

Clear communication skills

Tools

LangGraph

Pydantic AI

C#

C++

Kubernetes

Job description

We tackle the most complex problems in quantitative finance by bringing scientific clarity to financial complexity. From our London HQ, we unite world‑class researchers and engineers in an environment that values deep exploration and methodical execution – because the best ideas take time to evolve.

Role

As part of our engineering team, you’ll shape the platforms and tools that drive high‑impact research – designing systems that scale, accelerate discovery and support innovation across the firm. The Applied AI team sits at the centre of this effort, building the AI layer that will transform how teams across the firm work, from quant research to engineering, risk and operations.

Key Responsibilities

• Work across areas such as retrieval and knowledge systems, multi‑agent orchestration, evaluation, reliability and context engineering.
• Take AI systems from early prototypes to trusted, production‑ready solutions.
• Own high‑impact projects from initial concept through to production.
• Partner with teams across the firm to identify problems and deliver scalable solutions.
• Turn team‑specific use cases into solutions that can be adopted more widely across the organisation.

Qualifications

• Strong software engineering background with modern AI technologies.
• Hands‑on experience building LLM‑powered systems in production, including agents, RAG pipelines, MCPs, tool‑use and multi‑step workflows.
• Familiarity with frameworks such as LangGraph, Pydantic AI or similar.
• Strong Python engineering skills and ability to produce clean, testable, production‑quality code.
• Experience with context engineering: retrieval strategies, prompt construction, information routing, memory.
• Experience with evaluation and observability for AI systems, including measuring accuracy, detecting regressions and understanding failure modes.
• Ability to work across domains; comfortable embedding with quantitative research teams one month and ops teams the next.
• Clear communication skills.
• Experience with fine‑tuning or adapting foundation models (e.g., LoRA, DPO).
• Comfort integrating with heterogeneous stacks such as C#, C++, JVM, gRPC, Kubernetes.
• Contributions to open‑source AI projects, technical writing or conference talks.

Benefits

• Highly competitive compensation plus annual discretionary bonus.
• Lunch provided (via Just Eat for Business) and dedicated barista bar.
• 35 days annual leave.
• 9% company pension contributions.
• Informal dress code and excellent work/life balance.
• Comprehensive healthcare and life assurance.
• Cycle‑to‑work scheme.
• Monthly company events.

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