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Open nowPosted 22 days ago

Staff Software Developer

Enovix Corporation28 open roles

Where
Penang, MY
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Your applicationOpen nowStaff Software DeveloperEnovix Corporation · Penang, MY

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  5. 35.6%30 days
  6. 58.0%60 days
This job: posted 22 days ago

The posting

Senior Principal Software Developer, IT/OT (MES & Factory Systems)

Job Summary

The Principal Software Developer, IT/OT is the senior individual-contributor technical authority responsible for designing, developing, and governing mission-critical software systems that integrate enterprise IT platforms with industrial Operational Technology (OT) environments, with the Manufacturing Execution System (MES) as the core platform of ownership. This role combines deep hands-on engineering expertise — particularly in Python, Django, and SQL — with architectural leadership and solution design across manufacturing systems, automation platforms, cybersecurity boundaries, cloud infrastructure, and applied AI/ML. The individual translates business needs into scalable system enhancements, designs and refines interfaces and automation workflows, and ensures high-quality solution delivery through rigorous testing and documentation. This role requires close collaboration with application, infrastructure, and business teams to deliver reliable solutions that improve shopfloor efficiency and overall system performance.

Core Expertise

Candidates must be well-versed in the following areas, which form the technical core of this role:

  • Python — expert-level scripting and application development
  • Django framework — expert-level, production experience (Flask and SQLAlchemy familiarity a plus)
  • SQL — expert across systems: complex queries, common table expressions, temporary tables, and query performance tuning
  • MES — hands-on ownership of Manufacturing Execution System platforms and their factory-system integrations
  • Solution Design — enterprise/system architecture, IT/OT convergence design, and edge-to-cloud integration patterns
  • AI Programming & Development — applying machine learning and AI-assisted engineering practices to manufacturing data, quality analytics, and the software delivery lifecycle

Responsibilities

Solution Design & Enterprise Software Development

  • Architect and implement distributed systems and solution designs supporting manufacturing operations.
  • Design high-throughput, low-latency data acquisition and processing pipelines.
  • Develop backend services, APIs, middleware, and integration layers, primarily in Python/Django.
  • Lead refactoring and modernization of legacy OT software systems.
  • Ensure deterministic, fault-tolerant system behavior for critical production environments.

MES & IT/OT System Integration

  • Own and develop the MES and its integrations with SCADA, ERP, and PLM platforms.
  • Build integration frameworks for OPC UA, MQTT, Modbus, SECS/GEM, and RESTful services.
  • Design edge-to-cloud data synchronization models and event-driven/microservices architectures.
  • Enable real-time production telemetry and operational analytics.

AI & Intelligent Automation

  • Design and develop AI/ML-driven features for predictive quality analytics, anomaly detection, and process optimization using production and SPC data.
  • Integrate AI/LLM-based tools and APIs into MES workflows and internal tooling to accelerate diagnostics, documentation, and decision support.
  • Evaluate and adopt AI-assisted software development practices (AI coding assistants, automated code review and test generation) to improve delivery speed and code quality.
  • Partner with Quality and Data teams to build data pipelines suitable for ML model training and inference in a manufacturing environment.

Quality & SPC Systems Support

  • Support integration between manufacturing systems — including measurement data — and SPC platforms.
  • Develop data acquisition pipelines for process capability monitoring; implement real-time rule-based alerts and control chart logic.
  • Collaborate with Quality Engineering on Cp/Cpk monitoring, yield analysis, and audit traceability.

DevOps, Testing & Reliability Engineering

  • Establish CI/CD pipelines and full-coverage unit/system test suites for industrial software deployments.
  • Familiar with Infrastructure-as-Code, containerization (Docker, including Windows-based apps), and Azure-based deployment and configuration management.
  • Define observability standards (logging, metrics, tracing) and drive high-availability, disaster recovery, and redundancy design.
  • Own code deployment and server/IIS configuration troubleshooting.

Technical Leadership & Governance

  • Serve as enterprise subject matter expert in IT/OT software architecture and solution design; conduct architecture reviews and design approvals.
  • Establish engineering standards and best practices; provide executive-level technical briefings on modernization strategies, including AI adoption.
  • Write and maintain clear system-level documentation across the full software development lifecycle.

Operational Support & Service Ownership

  • Act as the technical escalation point for Root Cause Analysis (RCA) on production-impacting events; implement Corrective Action & Preventative Actions (CAPA).
  • Monitor logs, respond to alerts and user queries, and maintain production system stability in 24x7 manufacturing environments.
  • Ensure SLA adherence and manage competing priorities across project work and daily operational interruptions.

Service Requests & Change Management

  • Evaluate and implement service requests from Manufacturing, Engineering, and Quality teams; provide impact analysis and technical feasibility assessments.
  • Deliver minor enhancements, configuration updates, and performance tuning; manage change control aligned with IT standards.

Infrastructure Lifecycle & Platform Upgrades

  • Plan and execute application-compatible server patching; coordinate OS, middleware, and database patch deployments with staging validation.
  • Lead major version upgrades for MES, SCADA, and SPC platforms; coordinate vendor engagement and technical remediation.

Skills & Technical Expertise

  • Python — expert; Django framework (production systems) expert; Flask and SQL Alchemy — familiar.
  • SQL — expert, including complex queries, CTEs, temporary tables, and performance tuning across systems.
  • AI/ML programming — experience applying machine learning to software or manufacturing analytics (e.g., scikit-learn, pandas, PyTorch/TensorFlow, or similar).
  • Experience integrating LLM/AI APIs (e.g., OpenAI, Anthropic) into applications, automation, or developer workflows.
  • Familiarity with AI-assisted development tools (e.g., GitHub Copilot, Claude Code) to improve engineering productivity.
  • Working knowledge of prompt engineering and responsible AI/data-governance practices for production systems.
  • Vue 3 with Quasar framework for front-end development.
  • Web API development and integration (RESTful APIs, JSON, Webhook).
  • Industrial communication protocols: OPC-UA, SECS/GEM, MQTT, Modbus.
  • Troubleshooting and optimizing Siemens OpsCenter and SCADA systems.
  • Docker — building and containerizing apps, including Windows-based applications.
  • Azure — running containers, managing file storage, environment configuration (dev/test/prod), and scheduled IRM-labeling scripts.
  • IIS administration.
  • Jira administration and workflow automation (validation, notification, conditional next state).
  • Run Deck automation service.
  • Strong problem-solving, analytical, and systems-level thinking; excellent communication and teamwork.
  • Minimum 5 years of programming/development experience in a manufacturing environment.

Qualifications

  • Bachelor’s degree in Computer Science, Software Engineering, or equivalent.
  • 6+ years of software development experience, including 5+ years supporting factory systems in a manufacturing environment.
  • Experience in semiconductor, battery, automotive, or discrete manufacturing preferred.
  • Hands-on experience with SPC systems and quality analytics platforms.
  • Experience or strong interest in applying AI/ML techniques to manufacturing or software engineering problems is a plus.
  • Experience supporting production systems in high-availability, 24x7 environments.
  • Systems-level thinking across automation, networking, and software layers; strong incident response and structured problem-solving.
  • Expert-level business analysis, deployment, and project-management ability; skilled at writing unambiguous system documentation for developers and end users.
  • Self-motivated, detail-oriented, critical thinker; understands the true (lifetime) cost of applications beyond initial build.
  • Excellent verbal and written communication skills.
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