The Role
As a Systems Engineer, you will design and build infrastructure for software and hardware interactions, working closely with materials R&D and AI technologies.
Summary Generated by Built In
Radical AI is replacing an R&D process that currently takes 10+ years and $100 million to produce a single discovery. Our self-driving lab platform combines AI with autonomous robotics to run experiments, analyze results, and iterate—continuously, without human bottlenecks. For industries like aerospace, automotive, defense, energy, manufacturing, semiconductors, and space, that means breakthroughs in weeks instead of years.
This is a generalist software engineering role on the team building the core platform that powers our autonomous lab. Depending on where you plug in, you might own backend services, agent tooling, data and orchestration pipelines, internal platforms, or the infrastructure that keeps our systems observable and reliable in production.
What's non-negotiable: strong systems thinking, production instincts, and the ability to contribute across the stack. We're building software that controls and monitors physical systems in the real world — the bar for correctness and reliability is high.
We work across a deeply cross-disciplinary domain (robotics, ML, experimental automation), and one near-term priority involves hybrid cloud/on-prem deployments in customer environments. Engineers who've navigated those constraints will hit the ground running.
What You'll Work On
- Lab backend: experiment definitions, sample path-planning, long running durable task execution
- Data backend: database schemas, migrations, ETL pipelines, object storage + partition design
- Internal platforms: developer tooling, SDKs, shared services, service templates
- Observability and reliability: structured logs, metrics, tracing, production debugging (OpenTelemetry, Prometheus/Grafana)
- Hybrid infrastructure: cloud + on-prem, containerization, orchestration, infrastructure-as-code
- Agent capabilities and tooling: API integrations, code execution, scientific literature retrieval, workflow automation
- Scientific workflow orchestration: Bayesian optimization loops, experiment scheduling, long-running job execution, retries, idempotency
- Data pipelines for ingesting, transforming, and serving data to models and LLMs
What We're Looking For
- 5–6+ years of production software engineering experience; strong enough to design, build, and ship end-to-end
- Fluency in Go and/or Python; additional stack experience (TypeScript, Rust) is welcome
- Deep comfort with distributed systems: timeouts, retries, idempotency, partial failure, dead-letter queues, safe rollback
- Experience with concurrent and asynchronous programming — event loops, cancellation semantics, bounded queues, task orchestration under failure
- Solid networking fundamentals (especially important for potential on-prem deployment contexts)
- Containerization and cloud deployment experience (Kubernetes, AWS); comfort debugging Linux systems
- High ownership: you find problems before they find users and raise the bar for quality
Nice to have
- Experience with agentic systems or LLM workflows (tool-calling, context management, PydanticAI, LangChain)
- Experience with enterprise self-hosted storage solutions (Ceph/Rook, Longhorn, WEKA, VAST, TrueNAS)
- Ray framework experience
- Familiarity with MongoDB and gRPC
- CI/CD and DevSecOps experience (GitHub Actions, Gitlab Pipelines)
- Familiarity with embedded protocols (serial, I²C, Modbus), device virtualization, or microcontroller firmware
- Strong observability experience (Datadog, Prometheus, Grafana, ELK, distributed tracing)
- Frontend experience (TypeScript/Svelte/React) — real-time interfaces, state management, structured APIs
Work Arrangement
This role is based in our New York City lab, and we are in person 5 days per week.
What We Offer
A competitive compensation package also includes the best in benefits:
- Medical, dental, and vision insurance for you and your family, covered at 100%
- Mental health and wellness support
- Unlimited PTO and 14+ company holidays per year
- Company-wide end-of-year shutdown, including two weeks of paid time off
- 401K
- Equity
Radical AI is committed to equal employment opportunity regardless of race, color, ancestry, national origin, religion, sex, age, sexual orientation, gender identity and expression, marital status, disability, or veteran status.
Skills Required
- Strong systems programming experience in Python, Rust, or C++
- Familiarity with concurrent and asynchronous programming
- Experience with protocol-aware interfaces for serial, TCP, USB, I²C
- Design device orchestration layers for long-running procedures
- Experience building hardware simulation environments
- Designing fault-tolerant distributed systems
- Instrumenting code with structured logs, metrics, and traces
- Experience deploying in real lab environments
Am I A Good Fit?
Get Personalized Job Insights.
Our AI-powered fit analysis compares your resume with a job listing so you know if your skills & experience align.
Success! Refresh the page to see how your skills align with this role.
The Company
What We Do
Through the integration of artificial intelligence, engineering, materials science, and applied research, we are changing the way materials are designed, developed, and discovered. In doing so we are tackling the world's most pressing problems.
Why Work With Us
We know what we are doing is hard. Really hard. We like that. As a team of deep domain experts, we trust each other and all move with autonomy. It won’t always look perfect —that’s the price of moving fast. But we prize execution above all else.
