At a Glance
- Tasks: Lead the design and implementation of advanced AI systems using cutting-edge technologies.
- Company: Join a dynamic tech company at the forefront of AI innovation.
- Benefits: Enjoy competitive salary, health perks, and flexible hybrid working.
- Other info: Collaborate with global clients and grow your skills in a fast-paced environment.
- Why this job: Make a real impact in the evolving world of agentic AI and software architecture.
- Qualifications: 5-8 years in software engineering with a focus on AI systems and LLMs.
The predicted salary is between 60000 - 80000 £ per year.
- 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), Lang Graph, Crew AI, 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, Lang Smith, 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: Lang Graph, Crew AI, Llama Index, Haystack, or comparable frameworks.
- Expert‑level Python; strong backend development skills (Fast API, 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): Big Query, 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.
- #J-18808-Ljbffr
Senior AI Engineer employer: Acrotrend - A NowVertical Company
As a Senior AI Engineer at our London-based company, you will thrive in a dynamic hybrid work environment that champions innovation and collaboration. We offer competitive salaries, health benefits, and a commitment to your professional growth through ongoing learning opportunities, all while working on cutting-edge AI projects with global clients. Join us to be part of a forward-thinking team that values resilience, creativity, and the pursuit of excellence in the rapidly evolving field of AI.
Contact Details:
Acrotrend - A NowVertical Company Recruitment Team
StudySmarter Expert Advice🤫
We think this is how you could land Senior AI Engineer
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We think you need these skills to ace Senior AI Engineer
Some tips for your application 🫡
Show off your coding skills:When applying for a software engineering role, it's super important to showcase your coding skills. Make sure your CV includes your tech stack, any relevant programming languages you’re comfortable with, and examples of projects you've worked on. If you have a GitHub profile, link it up! We love to see code in action.
Tailor your portfolio:For a full-time role, we’d expect to see some solid examples of your work in your portfolio. Make sure to include at least two or three projects that highlight your problem-solving skills and your ability to work with different technologies. Focus on the projects that are most relevant to the position at Acrotrend - A NowVertical Company.
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How to prepare for a job interview at Acrotrend - A NowVertical Company
✨Brush Up on Your Coding Skills
For a full-time software engineering role, it's crucial that we stay sharp with our coding abilities. Expect technical questions that might involve solving problems on the spot or discussing algorithms. Practise on platforms like LeetCode or HackerRank to get comfortable with the types of questions that often come up.
✨Know Your Tools and Frameworks
Make sure we’re well-acquainted with the tools and technologies listed in the job description. Familiarise ourselves with any specific frameworks or programming languages mentioned. If Acrotrend - A NowVertical Company uses React or Node.js, for instance, be ready to discuss how we’ve used them in previous projects or coursework.
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Bring along a portfolio that highlights our best work. This could be code samples, GitHub repositories, or any side projects we’ve built. Make sure we can talk through our thought process for each project, especially the challenges we faced and how we solved them—this shows our problem-solving skills in action.
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While technical skills are key, full-time positions also require cultural fit. Be ready to discuss our previous experiences and how we handle teamwork, conflict, and deadlines. Brush up on the STAR method—Situation, Task, Action, Result—to clearly articulate our past experiences when discussing how we've contributed to a team.
