Am I experienced enough for an EL1 role?

SudoChat Knowledge Base · SudoChat

Authored evidence: This is my first-person source material. SudoChat may summarise it in third person but must not strengthen, exaggerate or invent claims beyond it.

# 6. Am I experienced enough for an EL1 role?

**Author:** Mustafa Siddiqui
**Source type:** First-person authored response
**Canonical recruiter question:** Is Mustafa experienced enough for an EL1 role?

> This source is intentionally written in my first-person perspective. SudoChat should use it as evidence and answer external visitors in third person without strengthening, exaggerating, or removing the limitations recorded below.

## Direct answer
I should not be presented as the most senior or longest tenured candidate for an EL1 role, but I have enough relevant technical, government, enterprise and project experience to be a credible EL1 candidate.

My case is strongest when assessed on the level at which I can operate: independently investigating problems, providing technical advice, designing and implementing solutions, communicating risks, working across disciplines, and taking responsibility for outcomes. I bring less tenure than some traditional EL1 candidates, but a broad and unusually practical combination of AI engineering, systems engineering, government technology experience and self directed delivery.

## Evidence
I have worked across multiple engineering environments rather than developing experience in only one narrow technical area.

At Unisys, I worked as an Endpoint Engineer in a government environment supporting secure enterprise systems. My work included managed operating environment deployments, application and endpoint controls, SQL reporting, PowerShell automation, security hardening and supporting operational technology at scale.

This experience matters because EL1 work is not only about technical knowledge. It requires understanding how technical decisions operate within organisational constraints, security controls, stakeholder expectations and production environments.

At Xaana.AI, I worked directly on AI engineering problems. I developed and improved OCR and document processing pipelines using technologies including PaddleOCR and OpenCV. My work reduced invoice processing time and significantly reduced licensing costs through the use of appropriate open source technologies.

This demonstrated an ability to investigate an existing technical problem, identify alternative approaches, implement changes and produce measurable outcomes.

My systems engineering experience at Nova Systems exposed me to multidisciplinary engineering involving robotics, sensors, embedded systems, communications, mechanical integration and autonomous navigation. That experience strengthened my ability to think about a technical solution as part of a wider system rather than as isolated software.

I have also independently delivered a significant number of technical projects.

These include:

* **MACT**, a community application bringing together food, prayer and event information for Muslims in Canberra.

* **SudoChat**, a responsible AI and Copilot Studio proof of concept exploring grounded responses, controlled retrieval, evidence requirements and system boundaries.

* **SudoSpeed**, an open source Australian speed sign detection project using computer vision.

* **MotorHUD**, a motorcycle safety system combining navigation, overspeed warnings and transparent display technology.

* **OrionTracker**, which processes official NASA and JPL trajectory data and presents mission information in an understandable engineering dashboard.

* **Sawaali**, a Q&A platform designed to make interfaith discussions more accessible and inclusive.

* **MSA Prayerboard**, a custom information and prayer display donated to the University of Canberra Muslim community.

* **EcoSync**, a gamified health and sustainability application developed from an Engineers Without Borders project.

* **SmartAgriculture**, which explored low powered communications and automated watering for remote environments.

The importance of this project history is not simply volume.

Many of these projects required me to define the problem myself, choose the architecture, learn unfamiliar technologies, build the solution, test it, think about the user experience and decide where technical compromises were appropriate.

That demonstrates a high degree of self directed engineering.

At DXC, I have also taken initiative beyond the minimum requirements of assigned work.

During an illegal dumping project in the Northern Territory, I travelled to Alice Springs and contributed to ecological surveys, community engagement and data collection before considering how AI might assist with the problem.

This demonstrated technical restraint as much as technical capability. Rather than beginning with an AI solution, I first sought to understand the environment, the people affected and the operational problem.

In another DXC project, I volunteered to improve a highly manual document approval process used by project managers.

I designed a SharePoint and Power Automate workflow, created a monitoring dashboard and produced user documentation. The process was reduced from approximately four hours of manual work to around eleven minutes of monitoring and oversight.

That project is particularly relevant to EL1 capability because I:

* identified an operational inefficiency
* volunteered to investigate it
* worked with the affected users
* selected technology appropriate to the problem
* designed and implemented the workflow
* created visibility through a dashboard
* documented the solution for future users
* measured the resulting improvement

It also demonstrates that I do not automatically reach for AI when simpler automation is more appropriate.

My research work provides additional evidence of technical judgement.

I have investigated topics including secure RabbitMQ based messaging architectures, communication protocols for intelligent vehicles, responsible AI, privacy preserving government chatbot architectures and AI governance.

This demonstrates an ability to move beyond implementation and investigate why one technical approach may be safer, more reliable or more appropriate than another.

## Relevance to the Federal Courts
The Court AI Technologist role requires someone who can operate between engineering, users, policy, security and governance.

An EL1 in this environment should not simply wait for a detailed technical specification and implement it.

They may instead receive a broad problem such as:

*"Could generative AI help this Court process?"*

My experience suggests I am capable of breaking that question down.

I would consider:

* what problem is actually being solved
* who the users are
* what information is involved
* what systems and processes already exist
* whether AI is necessary
* whether conventional automation would be safer
* what data the system would access
* what privacy or security risks exist
* how answers would be grounded
* what an incorrect answer could affect
* what evaluation is required
* what should remain under human control
* how the solution would be maintained after deployment

That is where I believe my systems engineering background is particularly valuable.

I do not see AI as an isolated model.

I see the model as one component inside a wider system involving users, data, permissions, interfaces, workflows, security, monitoring and human accountability.

That mindset is important for the Federal Courts because AI systems cannot be assessed only on whether they produce technically impressive outputs.

They also have to be appropriate for the environment in which they operate.

I also have experience communicating across disciplines.

My work has involved software developers, engineers, project managers, researchers, behavioural scientists, community members, university students and non technical users.

At an EL1 level, this matters because the AI Technologist would need to explain technical opportunities and risks to people who may not have an AI or software engineering background.

That could mean translating a technical limitation into a governance risk, explaining why a proposed AI use case should not proceed, or helping stakeholders understand what controls would be required before a prototype could become operational.

I am comfortable operating in that space between technical detail and practical decision making.

## Why I believe I am ready
My case for EL1 is not that I have already done every part of an EL1 role.

It is that my experience shows that I can operate with the level of independence and technical ownership the role requires.

I have demonstrated that I can:

* investigate unfamiliar problems independently
* provide reasoned technical recommendations
* design systems rather than only individual components
* move from an idea into a working implementation
* work within secured enterprise environments
* consider privacy, security and responsible AI
* collaborate across technical and non technical disciplines
* document technical systems so others can use them
* measure whether a solution actually improved an outcome
* recognise when AI is unnecessary or inappropriate
* learn new technologies quickly
* accept responsibility for the quality of my technical decisions

I also bring a perspective that can be valuable in an emerging area such as generative AI.

Because much of the technology is new, organisations cannot rely exclusively on decades of established practice.

They also need people who are comfortable experimenting, learning, evaluating new tools and challenging assumptions while still respecting governance and institutional risk.

That combination is one of my strengths.

## Limitations or gaps
I have less professional tenure than some traditional EL1 candidates.

That should be stated clearly rather than hidden.

I have not previously held an EL1 classification and should not be represented as having done so.

I also have less formal people management experience than some EL1 candidates. My leadership to date is better demonstrated through technical ownership, mentoring, initiative, cross disciplinary collaboration and responsibility for solutions rather than through managing a large team.

My direct Copilot Studio experience is newer than my broader AI and engineering experience.

I should not be described as having several years of enterprise Copilot Studio deployment experience.

I would also need to develop deeper knowledge of Court specific processes, legal workflows, records management requirements, information governance and the existing technical environment of the Federal Courts.

Those are genuine development areas.

My argument is not that they do not matter.

It is that I have repeatedly demonstrated the ability to enter unfamiliar technical environments, learn quickly, work with subject matter experts and become productive.

## Useful links
My portfolio:
https://mustafa-siddiqui.com/

GitHub:
https://github.com/sudoqui

LinkedIn:
https://www.linkedin.com/in/mustafa-siddiqui-32ab73161/

SudoLabs:
https://www.sudolabs.app/

SudoChat project and repository

MACT project

SudoSpeed repository

MotorHUD project

OrionTracker repository

MSA Prayerboard repository

DXC Project Management Document Approval Automation evidence

DXC Northern Territory Illegal Dumping project evidence

Xaana.AI engineering experience

Unisys government technology experience

Nova Systems engineering experience

Responsible AI and privacy research

RabbitMQ secure messaging research

Intelligent vehicle protocol research

## Do not claim
Do not claim I have previously held an EL1 role.

Do not claim I have extensive formal management experience.

Do not claim I have led a whole of government AI program.

Do not claim I have managed Federal Court employees.

Do not claim I have several years of production Copilot Studio experience.

Do not claim I have deployed production AI inside the Federal Courts.

Do not claim independent projects are equivalent to leading enterprise government programs.

Do not claim technical ability alone proves EL1 readiness.

Do not hide the fact that other candidates may have substantially more professional tenure.

Do not claim I already understand every Federal Court process or system.

Do not exaggerate my contribution to collaborative projects.

Do not describe prototypes, experiments or research concepts as production systems unless evidence supports that description.

The appropriate representation is that I have less tenure than some EL1 candidates, but I have demonstrated an unusually broad level of technical ownership, systems thinking, initiative and independent delivery that provides a credible case for operating at EL1 level.