At a Glance
- Tasks: Build cutting-edge AI agents that think, plan, and act in real-time environments.
- Company: Join an early-stage, venture-backed AI startup with a dynamic team.
- Benefits: Competitive salary plus meaningful equity and growth opportunities.
- Other info: Fast-paced environment with direct collaboration with founders.
- Why this job: Be at the forefront of AI innovation and make a real impact.
- Qualifications: Experience in software engineering and a passion for AI technologies.
The predicted salary is between 60000 - 80000 € per year.
Key Details
- Location: Reading
- Compensation: Competitive salary + meaningful equity
- Stage: Early-stage, venture-backed AI startup
- Team: Working directly with founders and early engineering team
Overview
We’re building autonomous AI agents that perceive, reason, plan, and act across live environments. This is not a prompt-engineering role. You’ll build production-grade agent systems capable of navigating interfaces, using tools, orchestrating workflows, recovering from failure, and operating reliably at scale. We’re looking for engineers who can bridge frontier AI research with hardened distributed systems. You’ll work directly with founders to define the architecture, infrastructure, and operational backbone behind next-generation AI agents.
Key Responsibilities
- Build autonomous AI agents using modern agent frameworks such as LangGraph, OpenAI Agents SDK, AutoGen, CrewAI, or similar orchestration tooling
- Design multi-agent systems with planning, memory, tool use, routing, reflection, and long-running execution
- Develop agents powered by frontier LLMs and VLMs
- Build retrieval pipelines using vector databases such as Pinecone, Weaviate, Chroma, pgvector, or Milvus
- Engineer production AI infrastructure using Python, FastAPI, TypeScript, gRPC, event-driven systems, and async architectures
- Deploy and scale agent systems using Docker, Kubernetes, Helm, Terraform, AWS/GCP, and modern CI/CD pipelines
- Build observability and evaluation systems using LangSmith, Weights & Biases, MLflow, OpenTelemetry, Grafana, or custom telemetry pipelines
- Own model serving, inference optimisation, batching, caching, and GPU orchestration using tools like vLLM, Ray Serve, Triton, or BentoML
- Develop feedback and evaluation loops using RLHF, SFT, synthetic data generation, automated evals, and human-in-the-loop systems
- Build agents that interact with APIs, browsers, game engines, desktop environments, or mobile systems using Playwright, Selenium, browser automation, or custom tooling
- Solve hard production problems around hallucinations, memory drift, latency, concurrency, recovery, and agent reliability
- Operate with high ownership in a fast-moving startup environment with ambiguity and technical depth
Next Steps
If this sounds like your kind of challenge, we’d love to hear from you. The process is designed to move quickly and give you real exposure to the team, technical problems, and opportunity:
- Introductory conversation with the hiring managers / founders
- Collaborative Conversation around product, scaling, and engineering approach
Applied AI Engineer - Agentic in Reading employer: Experis
As an early-stage, venture-backed AI startup located in Reading, we offer a dynamic work environment where innovation thrives and every team member has a direct impact on our cutting-edge projects. Our culture fosters collaboration with founders and a passionate engineering team, providing ample opportunities for personal and professional growth while working on groundbreaking autonomous AI technologies. With competitive compensation and meaningful equity, we are committed to building a workplace that values creativity, ownership, and the pursuit of excellence.
StudySmarter Expert Advice🤫
We think this is how you could land Applied AI Engineer - Agentic in Reading
✨Tip Number 1
Network like a pro! Reach out to people in the AI field, especially those who work at startups. Use platforms like LinkedIn to connect and engage with them. You never know when a casual chat could lead to a job opportunity!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects related to AI agents or distributed systems. This is your chance to demonstrate what you can do beyond your CV. Make sure to share it during interviews or networking events.
✨Tip Number 3
Prepare for technical conversations! Brush up on the latest tools and frameworks mentioned in the job description, like LangGraph or Docker. Being able to discuss these topics confidently will set you apart from other candidates.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you're genuinely interested in joining our team and contributing to the exciting work we're doing in AI.
We think you need these skills to ace Applied AI Engineer - Agentic in Reading
Some tips for your application 🫡
Show Your Passion for AI:When writing your application, let us see your enthusiasm for AI! Share any projects or experiences that highlight your skills in building autonomous systems. We want to know what excites you about this field and how you can contribute to our mission.
Tailor Your CV and Cover Letter:Make sure your CV and cover letter are tailored specifically for the Applied AI Engineer role. Highlight relevant experience with agent frameworks and production-grade systems. We love seeing how your background aligns with our needs!
Be Clear and Concise:Keep your application clear and to the point. Use straightforward language to describe your skills and experiences. We appreciate a well-structured application that makes it easy for us to see your qualifications at a glance.
Apply Through Our Website:Don’t forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it gives you a chance to explore more about our team and culture.
How to prepare for a job interview at Experis
✨Know Your Tech Stack
Familiarise yourself with the technologies mentioned in the job description, like Python, FastAPI, and Docker. Be ready to discuss your experience with these tools and how you've used them in past projects.
✨Showcase Problem-Solving Skills
Prepare examples of how you've tackled complex production problems, such as latency or memory drift. Use the STAR method (Situation, Task, Action, Result) to structure your responses and highlight your critical thinking.
✨Understand Autonomous AI Agents
Dive deep into the concept of autonomous AI agents and be prepared to discuss frameworks like LangGraph or OpenAI Agents SDK. Show your enthusiasm for building systems that can operate reliably at scale.
✨Engage with Founders
Since you'll be working closely with the founders, demonstrate your interest in their vision. Ask insightful questions about the company's direction and how you can contribute to shaping the architecture and infrastructure.
