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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior AI Engineer - **Company:** Acrotrend - A NowVertical Company - **Location:** London, UK - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Microsoft Azure, BigQuery, Code Review, Continuous Integration, Extract Transform Load (ETL), Software Debugging, Software Design Patterns, Python (Programming Language), Node.Js, Pair Programming, Software Architecture, Azure Machine Learning, Search Technologies, Software Engineering, Unstructured Data, Pulumi, Dynamic Routing, Delivery Pipeline, Large Language Models, Multi-Agent Systems, Backend, Fastapi, Event Driven Architecture, Build Management, Kubernetes, Terraform, Azure Synapse Analytics, Data Pipelines, Automation Anywhere, Docker, Legacy Systems, Microservices - **Published:** September 10, 2026 - **Apply:** https://www.collegerecruiter.com/job/2840589830-senior-ai-engineer ## About the Role * 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. ## Description * 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. ## Related Videos - [Azure AI Foundry for Developers: Open Tools, Scalable Agents, Real Impact](https://www.wearedevelopers.com/videos/1541-azure-ai-foundry-for-developers-open-tools-scalable-agents-real-impact) - [Intro to FastAPI](https://www.wearedevelopers.com/videos/462-intro-to-fastapi) - [Why segmenting your infrastructure into tiers makes your infrastructure design better](https://www.wearedevelopers.com/videos/1960-why-segmenting-your-infrastructure-into-tiers-makes-your-infrastructure-design-better) - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [Agentic AI - From Theory to Practice: Developing Multi-Agent AI Systems on Azure](https://www.wearedevelopers.com/videos/1532-agentic-ai-from-theory-to-practice-developing-multi-agent-ai-systems-on-azure) - [Building and Deploying Multi-Agent Systems with ADK and Vertex AI](https://www.wearedevelopers.com/videos/1918-building-and-deploying-multi-agent-systems-with-adk-and-vertex-ai) ## Related Articles - [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [From Prototype to Production: Build AI Agents with This Free 4-Course Learning Path](https://www.wearedevelopers.com/magazine/655-from-prototype-to-production-build-ai-agents-with-this-free-4-course-learning-path)