At a Glance
- Tasks: Build cutting-edge AI agents that think, plan, and act autonomously.
- Company: Early-stage, venture-backed AI startup with a dynamic team.
- Benefits: Competitive salary, meaningful equity, and fast-paced growth opportunities.
- Other info: Work closely with founders in a collaborative and innovative environment.
- Why this job: Join us to shape the future of AI and tackle real-world challenges.
- Qualifications: Experience in software engineering and a passion for AI technologies.
The predicted salary is between 60000 - 80000 € per year.
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
- 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 employer: Experis
As an early-stage, venture-backed AI startup, we offer a dynamic work environment where innovation thrives and every team member has a direct impact on our groundbreaking projects. Our culture fosters collaboration with founders and the engineering team, providing ample opportunities for personal and professional growth while working on cutting-edge technology in autonomous AI. With competitive compensation and meaningful equity, we are committed to building a rewarding workplace that values creativity and ownership.
StudySmarter Expert Advice🤫
We think this is how you could land Applied AI Engineer - Agentic
✨Tip Number 1
Network like a pro! Reach out to folks in the AI space, especially those who are already working 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 just a CV. Make sure to highlight any relevant experience with tools mentioned in the job description.
✨Tip Number 3
Prepare for technical conversations! Brush up on your knowledge of modern agent frameworks and production AI infrastructure. Be ready to discuss how you would tackle real-world problems, as this will show you're not just about theory but can apply your skills practically.
✨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 building the next generation of AI agents.
We think you need these skills to ace Applied AI Engineer - Agentic
Some tips for your application 🫡
Tailor Your Application:Make sure to customise your CV and cover letter for the Applied AI Engineer role. Highlight your experience with autonomous AI agents and any relevant frameworks or tools you've used. We want to see how your skills align with our mission!
Showcase Your Projects:Include examples of projects where you've built or worked on AI systems, especially those that involve multi-agent designs or production-grade infrastructure. This gives us a glimpse into your hands-on experience and problem-solving abilities.
Be Clear and Concise:When writing your application, keep it straightforward and to the point. We appreciate clarity, so avoid jargon unless it's necessary. Make it easy for us to see why you're a great fit for our team!
Apply Through Our Website:We encourage you to submit your application directly through our website. This helps us streamline the process and ensures your application gets the attention it deserves. Plus, it’s super easy!
How to prepare for a job interview at Experis
✨Know Your Tech Inside Out
Make sure you’re well-versed in the technologies mentioned in the job description, like Python, FastAPI, and Docker. Brush up on your knowledge of agent frameworks and distributed systems, as you’ll likely be asked to discuss how you would implement these in real-world scenarios.
✨Showcase Your Problem-Solving Skills
Prepare to discuss specific challenges you've faced in previous roles, especially those related to AI agents or production systems. Think about how you approached problems like latency or memory drift, and be ready to explain your thought process and solutions clearly.
✨Engage with Founders' Vision
Since you’ll be working closely with the founders, it’s crucial to understand their vision for the company and the technology. Research the startup's goals and be prepared to share your thoughts on how you can contribute to building autonomous AI agents that align with their mission.
✨Ask Insightful Questions
Interviews are a two-way street! Prepare thoughtful questions about the team dynamics, the challenges they face, and their approach to scaling AI systems. This shows your genuine interest in the role and helps you gauge if the company is the right fit for you.
