Prompt Engineer – Industrial AI (Oil & Gas / Mining)
At AIEngineer (AIEngr.io), we’re creating a domain-specific AI Engineer — designed for real-world industrial problems in Oil & Gas and Mining.
NOT a chatbot.
NOT generic AI.
We are building the future of industrial intelligence — not generic AI, but deeply contextual, engineering-grade AI that could give very specific and highly accurate answers.
And we’re looking for a Prompt Engineer who can help architect the intelligence layer behind it.
Role Overview
We are seeking a highly analytical and technically grounded
Prompt Engineer
to design, optimize, and scale prompt architectures that power our industrial AI systems.
This is not a generic chatbot role. You will be engineering AI reasoning frameworks for:
- P&ID interpretation
- Process design calculations
- Standards mapping (IEC, API, ISO)
- Root cause analysis
- Operations troubleshooting
- OT cybersecurity use cases
- Engineering document intelligence
You will work at the intersection of:
- Generative AI
- Industrial engineering knowledge
- Structured reasoning systems
- AI evaluation and safety frameworks
Key Responsibilities
Ø
Prompt Architecture & Design
· Design structured prompt templates for engineering reasoning workflows
· Develop multi-step reasoning frameworks (Chain-of-Thought, Tree-of-Thought, Tool-augmented reasoning)
· Build reusable prompt libraries for:
o Process engineering
o Mechanical systems
o Instrumentation & control
· Optimize prompts for accuracy, determinism, and technical depth
Ø
Domain-Specific AI Training
· Translate engineering standards into structured AI instructions
· Convert real engineering problems into training-grade prompt scenarios
· Improve AI capability in:
o Design basis generation
o Equipment sizing logic
o Cause & effect validation
o SIL verification reasoning
o Shift handover intelligence
Ø
AI Evaluation & Quality Control
· Build evaluation frameworks for:
o Technical correctness
o Standards compliance
o Hallucination detection
o Safety-critical outputs
· Develop benchmark test suites for industrial queries
· Run red-team testing on high-risk engineering outputs
Ø
Tool & Workflow Integration
· Work with developers to:
o Integrate retrieval-augmented generation (RAG)
o Connect AI to structured engineering databases
o Improve document parsing intelligence (P&ID, datasheets, HAZOP reports)
· Optimize token efficiency and latency-performance trade-offs
Ø
Continuous Model Optimization
· Experiment with prompt tuning techniques
· Evaluate model performance across GPT, Claude, open-source LLMs
· Improve domain specificity and reduce generic responses
· Create version-controlled prompt systems
Required Qualifications
Technical
- Strong understanding of LLMs and prompt engineering principles
- Experience working with GPT-class models
- Experience with:
- RAG pipelines
- Vector databases
- Structured prompting
- JSON schema outputs
- Ability to think in structured reasoning trees
