Software Architect

Our client is a global mining company securing the critical minerals behind the energy transition, including copper, cobalt, nickel, tin, and rare earths; they invest in and operate premium mining assets.

They are seeking an experienced Software Architect with strong expertise in industrial automation, mining platforms, or industrial digital solutions and modern AI-enabled software architectures. The ideal candidate should have hands-on experience in designing scalable industrial software platforms that integrate with OT systems, edge devices, process historians, cloud services, and enterprise applications.

The role requires a strong understanding of industrial communication protocols, data acquisition systems, process historians, edge computing platforms, and industrial integration patterns, along with practical experience of AI, MCP servers, agentic AI frameworks, and LLM-based industrial assistants.

The Software Architect will be responsible for defining the solution architecture, technical direction, integration patterns, platform standards, and engineering best practices for industrial digital platforms. This is a hands-on role and the successful candidate will be expected to continue writing code alongside the engineering team.

Key Responsibilities

1. Platform & Solution Architecture

• Design and implement scalable, secure, reliable, and maintainable software systems for industrial automation and digital transformation platforms.
• Architect industrial computing and edge platforms that can operate reliably in constrained, remote, underground, or low-connectivity environments.

2. Industrial Integration & Data

• Support integration with IoT devices, industrial gateways, telemetry systems, PLCs, SCADA/DCS systems, sensors, and equipment data sources.
• Define data acquisition, normalization, contextualization, storage, and data governance strategies for industrial operational data.
• Design architecture for real-time and historical data pipelines involving industrial protocols, streaming platforms, historians, relational databases, time-series databases, and graph databases.

3. AI-Enabled Industrial Applications

• Contribute to the architecture of AI-enabled industrial applications, digital assistants, copilots, and operational intelligence solutions.
• Design secure integration patterns for LLMs, MCP servers, tools, agents, knowledge bases, enterprise systems, and industrial data platforms.
• Define how industrial data, asset models, historians, graph databases, and operational systems can be safely exposed to AI agents with proper access control, traceability, and governance.

4. Technical Governance & Collaboration

• Review solution designs, architecture documents, code quality, integration approaches, platform decisions, and technology selections.
• Collaborate with product owners, business stakeholders, and customer teams to translate operational requirements into robust technical solutions.

Key Qualifications

• 15+ years' experience in industrial automation, industrial or mining digital platforms, or integration of IT/OT systems.
• Strong hands-on experience in C# / .NET for building scalable industrial software platforms, backend services, APIs, and integration services. (Mandatory)
• Experience with industrial IoT or IoT platforms, and with microservices architecture. (Mandatory)
• Hands-on experience developing MCP servers and working with agentic AI frameworks, together with a working knowledge of LLMs and how to use them. (Mandatory)
• Experience with Kafka/MQTT/RabbitMQ or similar event-streaming platforms for real-time industrial data ingestion, event processing, and system integration.
• Experience with databases such as PostgreSQL, SQL Server, time-series databases, and Graph DBs.
• Experience with platforms for modelling industrial assets, relationships, workflows, and contextual data.
• Experience with identity and access management platforms such as Keycloak, including authentication, authorization, SSO, role-based access control, and integration with enterprise identity providers.
• Experience designing or contributing to industrial AI assistants, copilots, or operational intelligence solutions.
• Knowledge of LangGraph, LangChain, OpenAI Agent SDK, AWS Bedrock, Azure AI, or similar AI platforms and frameworks.
• Understanding of knowledge graphs, semantic models, graph databases, and industrial asset models.
• Exposure to industrial use cases such as root cause analysis, production variance analysis, equipment health insights, predictive maintenance, process optimization, and operational copilots.
• Familiarity with secure AI integration patterns, including permission controls, tool access governance, auditability, and human approval workflows.