About
I build systems where software meets actual operations.
I help organizations use software and data to change how work gets done.
I’m Benjamin Mulenga — a systems and software engineer. My work spans systems engineering, software development, data platforms, AI, automation, and the decision surfaces that connect them.
Mining is one demanding proof ground — not the boundary of my work. Building around live production systems taught me to value visible state, honest failure, practical interfaces, and complexity that has to justify itself.
The difference is the combination — physical operations, software, data, automation, AI and decision systems. Operational software usually fails in the gaps between them. That gap is where I work.
How I work
Four habits, every project.
- 01
Observe the operation
Find the decisions, delays, failure modes, and human workarounds the software must respect.
- 02
Model the constraint
Turn assumptions into data, rules, and a small testable model before committing to a large build.
- 03
Ship the system
Build the interface, services, data paths, and controls as one working operational loop.
- 04
Keep it observable
Make state, failure, recovery, and ownership visible after the software enters real work.
40%lower reporting latency
- Context
- Operational Power BI and SSRS reporting inside a live mining environment.
- Baseline
- The previous reporting path took longer to move production information into decision-ready reports.
- Intervention
- Redesigned the reporting layer and its production data pipelines.
- My role
- Data-system design, implementation, and operational support.
- Verification
- Observed against the previous production reporting path. Internal records and absolute timings are confidential.
15%reduction in equipment idle time
- Context
- Equipment information moving through operational reporting and follow-up workflows.
- Baseline
- Manual and delayed information flows slowed action around idle equipment.
- Intervention
- Introduced Python and SQL automation to improve information speed and consistency.
- My role
- Automation design, data engineering, and delivery.
- Verification
- Reported operational outcome from the improved workflow. Measurement records and attribution detail are not public.
<1hrecovery path, down from four hours
- Context
- Disaster recovery for systems supporting continuous mine operations.
- Baseline
- The documented recovery path was approximately four hours.
- Intervention
- Rebuilt and exercised recovery procedures around operational continuity.
- My role
- Recovery-path design, procedure implementation, and validation.
- Verification
- Documented and exercised recovery path. Infrastructure detail is withheld for security.
5+ yrsinside production operations
- Context
- A 24/7 industrial environment where software and data failures affect physical work.
- Baseline
- Experience spans production IT, data engineering, automation, reporting, and recovery.
- Intervention
- Continuous delivery and support across operational systems rather than a single project.
- My role
- Systems engineer, software developer, data engineer, and automation builder.
- Verification
- Professional operating context; sensitive employer systems and records remain private.