Help turn business needs into reliable AI applications, data workflows and model inference services.
HT Telecom Pty Ltd, trading as HT Broadband, welcomes expressions of interest from AI and data engineering professionals. Established in 2017, our 28-person team spans telecommunications, technical development, customer support and operations.
Our services include broadband, business voice, mobile connectivity, enterprise hardware, third-party data centre support and managed AI applications. We are planning the next stage of our data and AI capabilities around practical customer support, business communications and network operations workflows.
We welcome experience in one or more of these engineering areas.
Knowledge-based questions and answers using retrieval-augmented generation (RAG).
Customer support workflows, ticket classification and information retrieval.
With customer authorisation and appropriate data handling, speech transcription, call summaries and business workflow integrations.
Analysis of authorised network metrics, service alerts and business data.
Evaluation of suitable model APIs and locally deployable models.
Planning Australian GPU inference infrastructure, with capacity determined by application testing, budget and hosting conditions.
Local GPU nodes remain at the planning stage. Initial priorities are application validation, retrieval augmentation and model inference, with lightweight fine-tuning assessed where useful. Training foundation models from scratch is not an initial objective.
THREE TECHNICAL DIRECTIONS
Where you could make a difference.
Explore the responsibilities, relevant skills and experience for each direction.
01 / ENGINEERING
AI Applications & Integration Engineer
Turn language models and enterprise knowledge into useful, testable business applications.
AUD 170,000approx. annual base + Super
Responsibilities & experience ＋
Proposed responsibilities
Develop RAG workflows for product knowledge, support documentation and service tickets.
Integrate model APIs and deployable models into enterprise applications.
Build prototypes for ticket classification, call summaries and workflow automation.
Integrate AI features with authorised CRM, service ticketing and communications systems.
Establish evaluation datasets to test answer quality, response latency and task completion.
Implement human handover, exception handling and access controls for customer-facing workflows.
Document integrations and work with customer support and operations colleagues to improve the experience.
Relevant skills
Practical software development with Python or a similar language, including APIs, testing and version control.
Hands-on projects involving language model applications, retrieval workflows or business system integration.
Understanding of embeddings, document ingestion, retrieval quality and grounded answer generation.
Ability to evaluate model output and handle unreliable or incomplete responses.
Clear communication with technical and non-technical colleagues.
Helpful experience
Voice applications, speech processing, cloud PBX or SIP integration, CRM or ticketing systems, and enterprise workflow automation.
02 / ENGINEERING
Data Engineer / Analytics Engineer
Build reliable data foundations for operational analysis and AI applications.
AUD 145,000approx. annual base + Super
Responsibilities & experience ＋
Proposed responsibilities
Build pipelines for authorised network metrics, service tickets, product information and business data.
Implement data cleansing, deduplication, validation and quality checks.
Design datasets and retrieval indexes for reporting, knowledge retrieval and AI pilots.
Evaluate data warehouse or lakehouse options suited to business needs.
Support dashboards for service performance, revenue and cost analysis.
Prepare data for anomaly detection, fault correlation and capacity trend analysis.
Document data sources, access permissions, transformations and retention requirements.
Relevant skills
Practical SQL and data pipeline development experience.
Python or another suitable data processing language.
Familiarity with data modelling, ingestion, transformation and testing.
Understanding of access controls and appropriate handling of business and customer information.
Ability to turn operational questions into defined datasets and measurable analysis.
Helpful experience
Telecommunications data, time series analysis, observability, business intelligence, document indexing and data support for machine learning applications.
03 / ENGINEERING
AI Inference & Infrastructure Engineer
Evaluate and prepare reliable infrastructure for model inference and enterprise pilots.
AUD 155,000approx. annual base + Super
Responsibilities & experience ＋
Proposed responsibilities
Benchmark model APIs and locally deployable models against representative workloads.
Measure concurrency, latency, throughput, memory use and cost per task.
Assess GPU, CPU, memory, storage and networking needs before procurement decisions.
Evaluate inference serving approaches, model packaging and repeatable deployment.
Plan authentication, usage quotas, metering, monitoring, logging and backups.
Work with application engineers on isolated environments and operational handover.
Support deployment planning around rack, power, cooling and connectivity requirements.
Prepare operating documentation and staged acceptance checks for approved deployments.
Relevant skills
Experience with Linux, networking and containerised deployment.
Hands-on deployment or testing of machine learning inference workloads.
Understanding of model memory requirements and performance trade-offs.
Familiarity with monitoring, troubleshooting, access controls and service reliability.
Ability to recommend infrastructure configurations and capacity based on test evidence.
Helpful experience
GPU operations, model serving platforms, deployment automation, performance optimisation and data centre coordination.
HOW THE WORK WOULD PROGRESS
Start with a need. Build on evidence.
Practical validation guides each stage of the planned work.
01
Define requirements
Review business processes, available data and access permissions. Select valuable pilots and establish baseline costs, latency and accuracy.
02
Run limited pilots
Compare suitable APIs and locally deployable models. Test application integration, retrieval and speech workflows with authorised data and agreed success criteria.
03
Prepare deployment & operations
After budget approval and confirmation of hosting conditions, support controlled deployment with monitoring, backups, access management and human handover.
04
Improve & expand
Use utilisation, service quality, customer demand and operational cost to guide improvements and capacity expansion.
THE OUTCOMES WE WANT TO TEST
Engineering with a practical purpose.
Engineers will help define and measure these goals, with outcomes assessed through actual validation.
Customer support
Faster information retrieval, more consistent answers and efficient handover to people.
Business communications
Less manual note-taking and better follow-up after customer calls.
Network operations
More efficient fault diagnosis and capacity planning.
Business analysis
Clearer operational reporting and better visibility of service costs.
EXPRESS YOUR INTEREST
Bring your experience.
We welcome relevant professional experience, demonstrable project work, or both. You do not need to cover every technical direction.
We value practical problem solving, clear documentation, careful data handling and collaboration across engineering and business teams.
What to send
A CV or brief professional introduction.
The technical direction or directions that interest you.
One or two relevant projects, including your own contribution and any measured outcomes.
Portfolio or code repository links that you are able to share.
Your current location, preferred working arrangements and availability to start.
Email subject AI Careers - [Technical direction] - [Your name]
Share only material you are authorised to disclose. Please do not send customer data, account credentials or a former employer’s confidential information. Passport, driving licence or other identity documents are not required with your initial expression of interest.
These expressions of interest relate to our developing AI and data plans. Scope, level, location, working arrangements, employment or collaboration type, remuneration and potential start dates will be discussed as opportunities become defined. There is no fixed hiring headcount or committed appointment timetable.