Principal AI Engineer

About us

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 an enthusiastic and opinionated Principal AI Engineer to define how AI agents transform Engineering workflows across industries such as Manufacturing, Aerospace, and Semi-conductor. You'll be building the foundations 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 architect the Agentic stack within this wider ecosystem. You will build a production-grade platform that enables our Product teams, FDEs, and customers to compose advanced AI workflows safely, transparently, and reliably. You will set the strategic direction for our platform's critical infrastructure and lead key implementation efforts. You are someone with the scar tissue of running agents in production. You have strong, reasoned opinions on emerging open standards (such as MCP, A2A, and ACP) and deep expertise in complex architectural patterns like durable execution and agent memory. You are passionate about building a world-class developer experience that transforms complex research into robust, deployed engineering solutions. Core Responsibilities

You will serve as the principal architect for our Agentic ecosystem, responsible for the high-level design choices that define how agents run at PhysicsX. You will cover topics such as

Agent Observability

Own the implementation to enforce deep tracing, granular cost tracking, and observability across the lifecycle.

Agent Deployment

Deliver an intuitive deployment lifecycle which simplifies questions around auth, discoverability and resource requirements.

Agent Sandboxing

Architect secure environments to isolate and allow agents to operate safely.

Agent Evals

Implement a stack that empowers domain experts to efficiently annotate traces, turning qualitative feedback into quantitative, reproducible evaluation datasets.

Agent Governance

Implement robust identity and access patterns to ensure agents can safely and correctly act on behalf of users in a regulated enterprise environment. The Tech Stack

Core Platform

Python (Primary), Go or TypeScript (Secondary), Kubernetes, Docker, Terraform.

Agentic Infrastructure

LangGraph/LangChain, Temporal (Durable Execution), Vector DBs (Pinecone/Weaviate).

Observability & Evals

OTel, LangSmith, Arize, Braintrust.

Who You Are

An Architect at Heart

You have strong, reasoned opinions on Durable Execution vs. Standard Async , Vector Search vs. Keyword Search , and Prompt Management strategies .

Platform-First

You care deeply about the Developer Experience (DevEx) of the Customers, FDEs consuming your platform. You build tools that make the "right way" the "easy way."

Security-Minded

You understand the risks of allowing LLMs to execute code and access data, and you know how to mitigate them via rigid sandboxing and permissioning.

Qualifications

Platform & Backend Foundations

4+ years of experience in Platform Engineering, Backend, or SRE. Strong proficiency in Python/Go, Kubernetes, Docker, and IaC (Terraform).

Agentic & AI Engineering

Production experience designing Agentic architectures (chains, tools, memory). Familiarity with Agentic frameworks (LangGraph, PydanticAI) and patterns like durable execution. Understanding of LLM-specific lifecycle issues: non-determinism, systematic evals, and token-based cost tracking. Bonus Points Background in Engineering workflows or simulation platforms. Experience building internal developer platforms (IDPs). 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.