London United Kingdom Ref: 2038
Applied AI Engineer ×4 roles | Netherlands / UK | Hybrid
ABOUT THE COMPANY
Oxygen Digital is supporting a fast-growing B2B SaaS business in the industrial and operations space to hire four Applied AI Engineers across two product squads. The company is building genuinely AI-native features into a product used by large enterprise customers — maintenance teams, operations managers, and field technicians who rely on the platform day to day.
This is a build-and-ship mandate. The team is close to customers, moving fast, and looking for engineers who can raise the capability of everyone around them.
ROLE OVERVIEW
You will own a vertical slice of an AI-native product feature end-to-end — from interface to orchestration to deployment to observability. You will work in a mixed squad alongside existing product engineers and PMs, reporting into the Chief AI Officer.
Four engineers will be hired across two product squads. Occasional customer-site visits are part of the role, including industrial environments.
KEY RESPONSIBILITIES
- Design, build, and ship production LLM-powered product features — real users, real load, real failure modes
- Build and operate RAG pipelines that survive long-tail customer data, not just clean demos
- Design and ship agentic systems with tool calling, multi-step reasoning, agent memory, and human-in-the-loop guardrails
- Own the full stack: frontend (React/TypeScript), backend (Python/TypeScript), and deployment — commit to production
- Build and maintain evaluation harnesses for non-deterministic AI systems
- Instrument AI systems with proper observability and tracing
- Contribute to a mixed squad — bring non-AI-native colleagues up, engage directly with customers
PERSON SPECIFICATION
Essential — Full-Stack Engineering
- Genuinely full-stack: comfortable shipping at every layer — frontend, backend, and deployment infrastructure
- DevOps literate: can deploy your own work, reason about CI/CD, debug containers, read infrastructure-as-code. Fluent on Azure
- Strong Python in production codebases — you know the difference between a working demo and a reliable service
Essential — Applied GenAI
- Hands-on production GenAI experience post-2023: shipped LLM-powered features to real users at real load — not hackathons or internal tools
- RAG expertise: chunking strategies, embedding model selection, hybrid search, re-ranking, citation and provenance tracking
- Familiarity with Graph RAG and when it outperforms vector-only retrieval
- Agentic systems experience: tool calling, function orchestration, multi-step reasoning, retry and validation loops — frameworks matter less than the underlying judgement
- Eval-literate: able to design and maintain evaluation harnesses for non-deterministic systems — LLM-as-judge calibration, regression suites, agent trajectory scoring, cost-per-task tracking
- Prompt engineering at system level: structured outputs, JSON-mode reliability, token and context budget management
- Multi-provider fluency: shipped against Anthropic, OpenAI, and at least one open-weights model
Essential — Production Discipline
- Experience handling hallucinations, latency tails, rate limits, cost overruns, and silent failures in production AI systems
- AI observability and tracing: Langfuse, LangSmith, Braintrust, OpenTelemetry, or equaivalent
- Vector databases: Pinecone, Weaviate, pgvector, Qdrant — including embedding lifecycle management
Strongly Preferred
- Experience in a forward-deployed or customer-facing AI engineering role
- Day-to-day use of AI coding agents (Claude Code, Cursor, Windsurf) and a view on Spec-Driven Development
- Background in industrial, operations, maintenance, or vertical SaaS
Candidate Profile
- High agency — ships, doesn’t wait for perfect conditions
- Opinionated but coachable; cares whether the feature works, not just whether the code is elegant
- Comfortable in a mixed squad and willing to bring non-AI-native colleagues along
- Customer-curious — willing to join calls, visit sites, watch real users work
- Comfortable with ambiguity and evolving scope
HOW TO APPLY
Send your CV and a brief covering note to View email address on oxygendigital.ai quoting Applied AI Engineer in the subject line.
Salary: £110k – £120k + benefits
Location: London (fully remote) with some travel (20%)
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