About Nexus Black
IFS Nexus Black builds AI to solve hard problems for the industries that keep the world turning: up on power lines, down on factory floors, and out in the field. Our products — Resolve (field service and predictive maintenance), Flow (production planning), Comply (regulatory compliance) and Reason (analytical reasoning) — are used by technicians and engineers who cannot afford a tool that doesn't work first time. We pair 40 years of IFS industrial depth with the technical pace of a start-up, and we get results in weeks, not months.
The role
You’ll build the agentic systems behind our products: agents that reason and orchestrate, deterministic code that calculates, and every output traceable. You’ll ship production code from week one — and then watch a field technician use it on a customer site, because that’s where our engineering standard is set.
What you’ll do
-
Design and build agentic workflows — multi-step tool use, retrieval, and orchestration — using Claude, LangChain/LangGraph and whatever earns its place next.
-
Own evaluation. Define what "correct" means for a workflow, build eval harnesses and golden datasets, and hold the line: if it wouldn’t convince a 30-year veteran, it doesn’t ship.
-
Take features from prototype to production: observability, tracing (LangSmith), error handling, and reliability that survives week six, not just the demo.
-
Join customer ride-alongs and site visits — plants, hangars, the field — and bring what you learn straight back into the code.
-
Work with coding agents daily (Claude Code, Cursor) — they’re how we work, not a novelty — and keep making your own job smaller.
-
Contribute like an owner: PR reviews, design docs, and a culture of writing things down.
What you’ll bring
-
Production experience with LLMs — you’ve shipped systems using model APIs (Anthropic, OpenAI or similar), not just notebooks: system-level prompt design, agent architectures, tool use, RAG.
-
An evaluation habit. You’ve built eval pipelines — golden datasets, regression suites, LLM-as-judge where it’s honest — and you can tell a good demo from a system that holds up in production.
-
Strong software fundamentals: Python and/or TypeScript, Git, testing, CI, and the judgement to know when deterministic code beats a model call.
-
Comfort with ambiguity and pace — small team, broad remit, shipping over ceremony.
-
Curiosity about the physical world. Our users fix aircraft and keep grids running; you should want to understand their job well enough to build for it.
Nice to have
-
Retrieval infrastructure at scale (vector stores, hybrid search, reranking).
-
Fine-tuning or model-adaptation experience where it genuinely beat prompting.
-
Experience in industrial, field-service or other asset-heavy domains.
-
Open-source contributions or a portfolio of shipped AI systems.
Why Nexus Black
We’re a small team building AI that has to work the first time, because the people using it are forty feet up a utility pole. AI tooling isn’t a side experiment here — it’s how we work every day. If you want your code in the hands of people who keep the world running, we’d like to talk. Less talk. More impact.
#J-18808-Ljbffr
AI Engineer UK employer: Worky
Goldman Sachs is an exceptional employer, offering a dynamic work environment where innovation and collaboration thrive. As a VP in Site Reliability Engineering, you will benefit from a culture that prioritises professional growth, with ample opportunities to lead critical projects and enhance your skills in a fast-paced financial services setting. Located in a vibrant city, the company provides competitive benefits and a commitment to employee well-being, making it an ideal place for those seeking meaningful and rewarding careers.
