Software, Controls & Integration Engineer

Company Description Drill Insight is a premier provider of AI-powered technology services and digital subsurface solutions headquartered in Perth, Australia, with active operations and offices across the North Sea, UK, Middle East, Asia Pacific, and Australia — including strategic hubs in Dubai, Kuala Lumpur, and India.

At Drill Insight, we deliver Data-Driven Insights – Powered by AI. We specialise in developing hybrid machine learning (ML) models, generating subsurface intelligence, enhancing reservoir characterisation, optimising field development and drilling, and ultimately maximising production outcomes for our global clients.

Having successfully executed over US $22.6 million in contracts, our impact is driven by an elite team of 16 multidisciplinary experts spanning data science, artificial intelligence, geoscience, well engineering, reservoir engineering, geology, geophysics, and project management. Our strength lies in integrating traditional oilfield expertise with cutting-edge ML/AI and digital technologies, enabling unparalleled optimisation across subsurface, drilling, and production domains.

Our AI/ML-driven Field-Insights®, Well-Insights®, and Drill-Insights® platforms support Oil and Gas E&P companies’ planning, operational and digital objectives. Our integrated team of drilling engineers, geoscientists, and data scientists has delivered AI/ML solutions for Chevron, Woodside, Equinor, Aker BP, SNOC and others - helping operators forecast drilling hazards, extract insight from offset wells, refine drilling targets, trajectories, well placements, and improve well performance and deliverability across varied basin conditions. Our integrated solutions, Field-Insights®, Well-Insights®, and Drill-Insights®, can deliver measurable value through Field Development Planning, Cloud-Based Well Review Automation, and Real-Time Drilling Visualisation, Performance Evaluation, Benchmarking and Optimisation Platform.

We are looking for builders rather than title collectors—people who can work across disciplines, challenge assumptions, communicate clearly with drilling engineers and turn difficult operational problems into reliable production systems.

Oil and gas experience is valuable, but exceptional candidates from industrial AI, robotics, mining, autonomous systems, process control, aerospace or real-time optimisation are strongly encouraged to apply.

This is an opportunity to build the real-time inference platform, APIs, advisory dashboard, edge deployment, observability and OEM-approved integration pathway using industrial data and control protocols.

Please send your CV or LinkedIn profile, availability, and a brief description of the hardest technical system or model you have built to: [email protected]

Subject: AI Drilling Programme

A GitHub profile, technical paper, portfolio, architecture diagram or short project summary is welcome—but not mandatory.

The location and engagement model will be discussed with the shortlisted candidates.

DrillInsight is seeking a strong backend and real-time systems engineer to convert approved ML recommendations into a secure, observable and operationally credible advisory platform.

This role sits at the intersection of:

• backend software,
• real-time data,
• model deployment,
• industrial integration,
• edge computing,
• and drilling automation.

Key responsibilities

Real-time platform

• Build and maintain model-serving and optimisation APIs.
• Develop real-time ingestion services for approved rig-data streams.
• Implement buffering, timestamp alignment, latency monitoring and data-quality checks.
• Connect ML outputs to Drill-Insights® dashboard components.
• Display:

o current versus recommended parameters,

o confidence,

o hazard status,

o operating-envelope limits,

o and operator acknowledgements.

Controls and integration

• Implement an advisory and setpoint-handover state machine.
• Map approved outputs such as:

o WOB recommendation,

o RPM recommendation,

o flow recommendation,

o differential-pressure recommendation,

o ROP advisory,

o SPP envelopes,

o bit-walk and directional indicators.

• Support OPC-UA, WITS/WITSML, WebSockets, APIs or other OEM-approved interfaces.
• Build human-in-the-loop approval and override workflows.
• Implement communication-loss, low-confidence and bad-data fallback behaviour.
• Maintain complete audit logs of inputs, recommendations and operator actions.

Deployment and DevOps

• Containerise services.
• Configure development, test and production environments.
• Build CI/CD and automated testing.
• Implement monitoring, logging and health checks.
• Support edge or on-premises deployment.
• Establish rollback, recovery and release-control procedures.