At a Glance
- Tasks: Build AI agents that transform engineering workflows across various industries.
- Company: Deep-tech company revolutionising hardware innovation with AI-driven solutions.
- Benefits: Competitive salary, inclusive culture, and opportunities for professional growth.
- Why this job: Join a mission to empower engineers and push the boundaries of possibility.
- Qualifications: 3+ years in Applied AI or ML Engineering, with experience in deploying AI agents.
- Other info: Diverse and inclusive workplace committed to equal opportunities.
The predicted salary is between 48000 - 72000 £ per year.
PhysicsX is a deep-tech company with roots in numerical physics and Formula One, dedicated to accelerating hardware innovation at the speed of software. We are building an AI-driven simulation software stack for engineering and manufacturing across advanced industries. By enabling high-fidelity, multi-physics simulation through AI inference across the entire engineering lifecycle, PhysicsX unlocks new levels of optimization and automation in design, manufacturing, and operations — empowering engineers to push the boundaries of possibility. Our customers include leading innovators in Aerospace & Defense, Materials, Energy, Semiconductors, and Automotive.
The Mission
We’re looking for a hands‑on Senior Applied AI Engineer to build the AI agents that transform Engineering workflows across industries such as Manufacturing, Aerospace, and Semi-conductor. You will be building the advanced workflows that power next‑generation simulation and design tools used by industry‑leading engineering teams. Our platform allows Forward Deployed Engineers (FDEs) and customers to build and deploy deep learning surrogates that solve massive engineering challenges. Your mission is to build advanced Agentic workflows that drive real value for our customers across the Engineering industry.
Core Responsibilities
- You will work with our product teams and customers to build and deploy agentic functionality directly into our platform, as well as deeply integrate our capabilities into how our customers operate.
- You are an expert in building and orchestrating AI Agents. You know how to chain LLMs, tools, and data to solve complex reasoning tasks.
- You aggressively dogfood our tools to build production solutions, and you provide direct feedback to improve the Developer Experience.
- Collaborative: You excel at partnering with domain experts (e.g. Physicists) to understand their mental models and codify them into agents.
You will be the tip of the spear for our Agentic capabilities, proving what is possible and helping us productise it.
- Be "Customer Zero": Aggressively dogfood our internal platform. If the Developer Experience hurts, you are the first to flag it and help fix it.
- Build Advanced Agentic Workflows: Design and implement complex agents that leverage our surrogates and simulation tools to solve specific customer problems.
- Drive Product Strategy: Use your direct experience building solutions to identify common patterns across customers. You will help decide what functionality belongs in the platform vs. what stays in the application layer.
- Rigorous Evals & Tracing: You don’t just ship "vibes." You implement systematic evaluation loops and deep tracing to prove that your agents are reliable, robust, and improving over time.
The Tech Stack
- Languages: Python (Primary), Go or TypeScript (Secondary).
- Agentic Infrastructure: Agentic Frameworks, Vector DBs
- Observability: OTel, Agent Tracing / Evaluations tooling
Who You Are
- A Builder First: You judge your success by shipping working agents that solve real problems in production, not just by writing design docs.
- Strategic & Broad: You don’t just solve the problem in front of you; you look for the "generalisable proof-point" that informs the broader platform strategy.
- Empirical: You value systematic measurement over intuition. You believe that if you can’t trace it and eval it, you can’t ship it.
- Agentic Native: You have a deep spike in Agentic Systems. You are comfortable working with domain experts to translate their knowledge into deterministic tools and workflows.
Qualifications
- 3+ years of experience in Applied AI, ML Engineering, or Software Engineering.
- Proven experience building and deploying AI Agents or complex LLM workflows in production.
- Demonstrated ability to collaborate with Domain Experts to solve complex, domain‑specific problems.
We value diversity and are committed to equal employment opportunity regardless of sex, race, religion, ethnicity, nationality, disability, age, sexual orientation or gender identity. We strongly encourage individuals from groups traditionally underrepresented in tech to apply. To help make a change, we sponsor bright women from disadvantaged backgrounds through their university degrees in science and mathematics. We collect diversity and inclusion data solely for the purpose of monitoring the effectiveness of our equal opportunities policies and ensuring compliance with UK employment and equality legislation. This information is confidential, used only in aggregate form, and will not influence the outcome of your application.
Senior AI Engineer - Applied employer: Physicsx
Contact Detail:
Physicsx Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior AI Engineer - Applied
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those at PhysicsX or similar companies. A friendly chat can sometimes lead to opportunities that aren’t even advertised.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your AI projects and workflows. This is your chance to demonstrate how you can build advanced agentic systems that solve real problems.
✨Tip Number 3
Prepare for technical interviews by brushing up on your Python and AI knowledge. Be ready to discuss how you've tackled complex reasoning tasks and collaborated with domain experts.
✨Tip Number 4
Don’t forget to 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 the team.
We think you need these skills to ace Senior AI Engineer - Applied
Some tips for your application 🫡
Show Your Passion for AI: When writing your application, let your enthusiasm for AI and engineering shine through. We want to see how your experience aligns with our mission of pushing the boundaries of possibility in advanced industries.
Tailor Your Experience: Make sure to highlight your relevant experience in building and deploying AI agents. We’re looking for specific examples that demonstrate your ability to solve complex problems, so don’t hold back on the details!
Collaborate and Communicate: Since collaboration is key at PhysicsX, share instances where you’ve worked with domain experts or cross-functional teams. Show us how you can translate complex ideas into actionable solutions that drive value.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for this exciting opportunity to join our team!
How to prepare for a job interview at Physicsx
✨Know Your AI Agents Inside Out
Make sure you can discuss your experience with building and deploying AI agents in detail. Be ready to share specific examples of how you've solved complex problems using AI workflows, especially in production environments.
✨Collaborate Like a Pro
Since the role involves working closely with domain experts, prepare to demonstrate your collaborative skills. Think of instances where you've successfully partnered with others to translate their knowledge into actionable AI solutions.
✨Showcase Your Empirical Approach
Be prepared to talk about how you measure success in your projects. Discuss any systematic evaluation loops or tracing methods you've implemented to ensure the reliability and robustness of your AI agents.
✨Understand the Bigger Picture
The role requires strategic thinking, so come equipped with insights on how your work can inform broader platform strategies. Think about generalisable proof-points from your past experiences that could apply to PhysicsX's mission.