Own the work. Grow with the firm.

• Run discovery on site or remotely: map the workflow, the documents and the decisions, and agree what success means before anything is built.
• Build the system end to end where the client chose to run it: retrieval, agents, integrations and the interface.
• Write the acceptance tests with the client's experts, test against thresholds agreed up front, and report every failure.
• Hand over cleanly: code, prompts, tests and runbook in the client's repository, and their staff trained to run it.
• Turn what each engagement teaches into reusable patterns and offers.
• As a partner: win and lead engagements, shape what Techsider offers, and help choose who joins next.

• You've built and shipped software that people rely on, and you've put LLM, retrieval or agent systems in front of real users.
• Strong engineering in Python or TypeScript, and hands-on experience with at least one major cloud platform.
• You can sit with a client's experts and executives, find what matters to them and explain trade-offs plainly.
• You test before you claim: evaluation sets, thresholds and honest reporting of what doesn't work.
• You use AI coding tools such as Claude Code, Codex or Cursor, with judgement about what to check.
• You want to build a firm, not just hold a job: you'd rather own the outcome and the client relationship.

• Own positioning and messaging for each buyer and industry: the problem, the evidence Techsider can show, and the next step.
• Run the insights programme: plan, brief, edit and publish articles, guides and demos that show how the work is done.
• Grow visibility in search engines and AI assistants, and measure where Techsider is found and cited.
• Plan campaigns and events for priority sectors and regions, and pass each qualified conversation to the engineer who'll lead the work.
• Use AI tools to draft content, with a person checking accuracy, voice and the site's claim rules before anything is published.
• Track what produces enquiries and Fit Calls, and stop what doesn't.

• Experience marketing technical or professional services to business buyers.
• Writing that is clear, specific and checkable, and the discipline to cut a claim you can't support.
• Hands-on search and content experience, including how AI assistants find and cite sources.
• Comfort with analytics: you set up the measure before the campaign, and report what it shows.
• Enough technical curiosity to understand retrieval, agents and evaluation, and to explain them to buyers.

• Answer enquiries from the website and email, book Fit Calls and follow up.
• As client systems go live, log, triage and escalate support requests within the response times each contract sets.
• Watch how those systems serve their users, such as escalations, refusals and complaints, and raise patterns with the engineer responsible.
• Keep help content, FAQs and runbook notes current, so common questions are answered the first time.
• Help onboard client staff: schedule training, share guides and check in after launch.
• Route privacy, security and data requests to the right person the same day.

• Experience in client service or support, ideally for software or professional services.
• Clear, warm written English, because most of the work happens in writing.
• A habit of closing loops: you track every request until it's resolved.
• Comfort with support and ticketing tools, and curiosity about how AI systems behave.
• Judgement about when to escalate, and discretion with confidential information.

• Map each engagement to the rules it may touch where it's used, and flag what the client's own lawyers need to confirm. These include privacy law such as the Australian Privacy Principles and the GDPR, sector rules, and AI-specific law such as the EU AI Act.
• Prepare the evidence clients' risk and legal teams draw on for their impact assessments and AI registers, such as data-flow maps, test results and failure lists.
• Review data-transfer terms, region notes and vendor terms for each engagement.
• Keep the site's regulatory references and their review dates current.
• Brief engineers and evaluators on what must be tested and recorded, and bring in external legal advice when a question needs it.

• Experience in privacy, technology risk or regulatory work.
• The ability to read legislation and standards closely, and to say what they do and don't require.
• Plain-English writing: you can turn a regulation into a checklist an engineer will use.
• Familiarity with AI governance frameworks such as ISO/IEC 42001 or the NIST AI RMF.
• Judgement about when a question needs a lawyer.

• Your CV, as a PDF.
• A short note: why this role, and what you've built or done that shows it.
• Links to your work, such as GitHub, a portfolio or LinkedIn.

Please leave out identity documents, a photo, your date of birth, health or other sensitive information, and details of your current or past pay. We won't ask about your current or past pay.

You'll need the right to work in the country you work from.

A person reads every application. If there's a fit, we'll arrange a conversation about the work and the terms. Sending an application doesn't guarantee a role.