Client-Embedded Applied AI Engineer — Rapid Prototyping

Cloud People; Greater London; Hybrid; GBP 90,000 - 130,000; Full time

Job summary

Cloud People is London-based and operates an autonomous AI prototyping pod serving banking, insurance and fintech clients. You will embed with clients, assess environments and turn ambiguous needs into working AI prototypes within their environments.

The role focuses on communicating AI capabilities in plain terms while building real, production-ready demos that can be scaled into deployments, with a startup pace and ownership ethos.

Qualifications

• Strong applied AI/ML engineering background building LLM-based solutions in Python.
• Hands-on experience with LangChain and LangGraph, RAG pipelines and vector stores.
• Experience turning ambiguous client requirements into working prototypes in real environments.
• Genuinely client-facing, able to translate AI into business terms and shape opportunities.
• Solid software engineering fundamentals across REST APIs, Docker and Kubernetes.
• Financial services or regulated environments experience is a plus.
• Experience with NVIDIA inference stack (NIM, NeMo, Triton) and GPU-backed workloads.
• Familiarity with agentic patterns and tool or function calling.
• Background in consultancy, forward deployed, or customer engineering roles.
• Comfortable with startup pace and ownership over implementing client projects.

Responsibilities

• Embed directly with financial services clients, understanding workflows, pain points and where AI adds real value.
• Assess client environments, infrastructure and data availability to determine what is buildable.
• Turn ambiguous requirements into working AI prototypes inside the client environment.
• Own the technical relationship from discovery through the first delivery sprint, handing over to the delivery pod.
• Design and build LLM and agentic solutions using Python, LangChain and LangGraph, RAG pipelines and vector stores.
• Build tool using agent workflows with clean API contracts, deterministic responses and audit logging.
• Work with NVIDIA inference tooling such as NIM, NeMo and Triton for GPU-backed AI workloads where needed.
• Run demos, gather feedback, troubleshoot live and iterate quickly with users and stakeholders.
• Translate technical AI concepts into clear business language and shape practical opportunities clients will fund.
• Harden prototypes to production viability, containerising with Docker and Kubernetes.

Skills

Python

LangChain

LangGraph

Applied AI/ML engineering

LLM-based solutions

REST APIs

Tools

Docker

Kubernetes

NVIDIA Triton

NIM/NeMo

Job description

Cloud People is London-based and operates an autonomous AI prototyping pod serving banking, insurance and fintech clients. You will embed with clients, assess environments and turn ambiguous needs into working AI prototypes within their environments.

The role focuses on communicating AI capabilities in plain terms while building real, production-ready demos that can be scaled into deployments, with a startup pace and ownership ethos.