Senior AI Engineer
NowVertical
| Company | NowVertical |
| Category | Engineering |
| Location | London |
| Remote | On-site (inferred) |
| Employment | Not stated |
| Level | Senior |
| Salary | Not stated by the employer |
| Posted | 29 Jun 2026 |
| Last verified | 30 Jul 2026 |
| Source | Employer career page (workable) |
Description
Role : Senior AI Engineer Location: London, UK (Hybrid) Experience: 5-8 Years NowVertical is a publicly listed company on the TSXV headquartered at Toronto, Canada. We are a growing team, with operations in two regions - NA & EMEA and LATAM . We help clients transform data into business value with AI, fast. NowVertical Group empowers organizations to transform their data into actionable insights, driving strategic growth and innovation. At NowVertical, we provide advanced data solutions and services designed to achieve key objectives across various business functions. Our tailored approach ensures that we address the unique challenges and opportunities within each function, driving innovation, efficiency, and growth. Explore our specialized solutions and see how we can help your business thrive. Know more about NowVertical - www.nowvertical.com NowVertical is looking for a Senior AI Engineer to design, build, and scale agentic AI systems powered by modern Large Language Models (LLMs). Reporting to our Principal AI Engineer, you will take technical ownership of complex AI workstreams, mentor more junior engineers, and help shape NowVertical’s AI platform strategy. This is a deeply hands-on role. You will architect and ship production-grade AI systems—multi-agent orchestration, RAG pipelines, tool-augmented reasoning workflows—while working across GCP, Azure, and AWS. We value versatile engineers who can navigate multiple frameworks and cloud environments to build resilient, observable, and scalable AI applications. Requirements What you will do... 1. Agentic AI & Multi-Agent Systems Architect and lead the implementation of multi-agent systems using Google AI SDKs (Vertex AI Agent Builder), LangGraph, CrewAI, and other emerging orchestration frameworks. Design and build stateful, tool-augmented agents capable of advanced reasoning, long-term planning, and autonomous execution. Develop and document agent orchestration patterns including planner-executor, supervisor-worker, and hierarchical agent structures. Implement sophisticated memory systems (short-term, long-term, and cross-session contextual memory). Enable seamless cross-agent communication and multi-modal coordination. 2. LLM Applications & Orchestration Lead the delivery of production-grade LLM applications: RAG pipelines, specialised agents, and developer copilots. Integrate diverse tools, enterprise APIs, and legacy systems into agentic workflows. Design robust system prompts, dynamic routing logic, and AI guardrails using Vertex AI Model Garden or Azure AI Studio. Drive optimisation of AI workflows for latency, token cost, and output quality. 3. Platform & API Development Develop and own reusable AI microservices, agent frameworks, and standardised APIs. Contribute to core AI platform capabilities including model routing, centralised observability, and safety filters. Define and enforce engineering standards and best practices for AI development across the team. 4. Cloud Deployment & Production Systems Deploy and manage agent-based systems on GCP, Azure, and/or AWS using Docker, Kubernetes (GKE/AKS/EKS), and Cloud Run. Implement comprehensive monitoring and observability using Vertex AI Inspector, LangSmith, or Azure Monitor. Drive incident response and post-mortems for production AI system failures. 5. Technical Leadership & Mentoring Act as a technical lead on key AI engineering workstreams, shaping architecture and approach. Mentor and support more junior AI engineers through code review, design discussions, and pair programming. Collaborate with Principal AI Engineer and cross-functional teams (data, product, delivery) to align AI engineering with business outcomes. Stay at the forefront of the rapidly evolving agentic AI landscape and bring new approaches into the team. Qualification & Skills: Core AI Expertise (Required) 5–8 years of soft
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