Senior AI Engineer

Acrotrend - A NowVertical Company; Greater London; Hybrid; GBP 120,000 - 150,000; Full time

Benefits offered by this job

Competitive base salary

Health and wellness benefits

Flexible hybrid working (UK-based)

Exposure to global clients and cutting

Ongoing learning and development

Job summary

Acrotrend - A NowVertical Company in London seeks a Senior AI Engineer to architect and lead multi‑agent AI systems, focusing on RAG pipelines and agent orchestration for production environments.

You will own memory systems, tool integrations, and scalable deployments across cloud platforms, collaborating with cross‑functional teams to deliver robust, observable, and cost‑effective AI capabilities.

Qualifications

• 5–8 years of software engineering experience with 3+ years in AI/LLM in production.
• Proven track record shipping RAG pipelines, autonomous agents and multi‑step reasoning.
• Hands‑on with Google AI SDKs, Vertex AI, and/or Azure AI services.
• Strong orchestration knowledge (LangGraph, CrewAI, LlamaIndex, Haystack).
• Expert python and backend skills; experience with FastAPI, Go or Node.js.

Responsibilities

• Architect and lead multi‑agent systems using Google Vertex AI, LangGraph, and CrewAI.
• Design memory systems (short/long-term, cross‑session) and agent coordination.
• Develop and document agent orchestration patterns (planner‑executor, supervisor‑worker).
• Lead production‑grade LLM apps: RAG pipelines, specialised agents, copilots.
• Integrate enterprise APIs and legacy systems into agentic workflows.
• Define prompts, routing logic, and guardrails; optimise latency and cost.
• Deploy and manage agents on GCP/Azure/AWS with Docker and Kubernetes.
• Mentor junior engineers; collaborate with data, product and delivery teams.
• Contribute to core AI platform capabilities: observability and safety filters.

Skills

Python

LLM-based systems

RAG pipelines

Agent design patterns

Go/Node.js

FastAPI

Cloud platforms

Docker & Kubernetes

Vertex AI / Azure AI

GCP / AWS / Azure

Tools

Vertex AI

LangGraph

CrewAI

LlamaIndex

Haystack

Terraform

Pulumi

Docker

Kubernetes

BigQuery

Azure Monitor

Job description

Role

Senior AI Engineer

Location

London, UK (Hybrid)

Experience

5‑8 years

Responsibilities

• 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.
• 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.
• 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.
• 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.
• 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.

Qualifications

• 5‑8 years of software engineering experience, with at least 3 years focused on LLM‑based or AI systems in production.
• Proven track record building and shipping RAG pipelines, autonomous agents, and multi‑step reasoning chains.
• Strong hands‑on experience with Google AI SDKs, Vertex AI, and/or Azure AI services.
• Deep proficiency in orchestration stacks: LangGraph, CrewAI, LlamaIndex, Haystack, or comparable frameworks.
• Expert‑level Python; strong backend development skills (FastAPI, Go, or Node.js).
• Deep understanding of agent design patterns: planning, reflection, memory, and tool‑use.
• Experience integrating complex enterprise APIs and event‑driven systems into agentic workflows.
• Proven ability to trace, debug, and improve non‑deterministic, multi‑step AI reasoning pipelines.
• Strong instinct for building resilient, observable, and production‑ready AI systems.
• Strong familiarity with GCP and/or Azure core services: GKE, Cloud Run, Azure AI services.
• Infrastructure as Code experience: Terraform or Pulumi.
• Experience building automated evaluation and deployment pipelines for AI models (CI/CD).
• Vector databases (nice to have): Vertex AI Vector Search, Azure AI Search, Pinecone, Weaviate.
• Data pipelines (nice to have): BigQuery, Pub/Sub, Azure Synapse.
• ETL/ELT experience preparing unstructured data for RAG and fine‑tuning (nice to have).

Additional Skills & Mindset

• View LLMs as components within a larger system, not just standalone models, and thoughtfully consider architecture, reliability, and cost.
• Take ownership, drive outcomes, and elevate the engineering team.
• Bias toward production‑ready, resilient, and observable AI applications.
• Passionate about the evolving landscape of agentic AI and next‑generation software architectures.
• Comfortable across cloud platforms and navigating ambiguity in a fast‑moving consultancy environment.

Benefits

• Competitive base salary + performance incentives.
• Health and wellness benefits.
• Flexible hybrid working environment (UK‑based).
• Exposure to global clients, cutting‑edge AI projects, and a fast‑growing AI practice.
• Ongoing learning and development support.