Technical Program Manager
Triskele Labs · Melbourne
Triskele Labs is an Australian sovereign, independent, founder owned cybersecurity business, Melbourne CBD based, on a journey to be a leading provider of cybersecurity services done properly, built on purpose, culture and mission. We serve Government, Corporate and Enterprise clients across APRA regulated, highly regulated and public sectors while continuing to support the mid market.
Our services span managed detection and response, digital forensics and incident response, penetration testing and governance, risk and compliance. We build the tools and automations that run those services ourselves, with AI at the centre of how we build, and this role is how that program gets prioritised, delivered and kept moving.
The Technical Program Manager is an AI native role. Triskele Labs builds its internal tools and automations with AI doing the large majority of the work, and this role runs that program the same way: with AI as the primary instrument for analysis, planning, delivery management and reporting, and with a mandate to make the teams it works with faster. It is a forward looking, cutting edge role for someone who already works this way, not a program office role with AI added on.
The role owns the internal build program: the internal tools the DevOps team builds and the automations the Workflow Automation team builds, typically five builds in flight at any time. Working closely with the CTO, the Technical Program Manager decides which tools and automations get built and in what order. From there the role owns the full lifecycle under Triskele Labs' secure software development lifecycle (SSDLC): discovery and planning with the SMEs who own the process, design with the engineers who will build it, agile delivery, testing and UAT, and implementation through to measured adoption.
It is hands on. The Technical Program Manager does the business analysis on every build personally, using AI to map processes, draft and test requirements, model options, generate test plans and interrogate delivery data, and brings that same leverage to the teams. The role exists to speed delivery up by removing ambiguity, decisions and dependencies before they block a build. There are no direct reports; the role leads through the program. Compliance certification and non engineering internal projects sit with a separate Graduate Project Manager, whom this role will mentor on method and tooling.
What you will do
Prioritise with the CTO
- Maintain, with the CTO, a single prioritised forward plan of internal tooling and automation: what gets built, in what order and why
- Bring the analysis behind each decision, built with AI and checked by you: the problem it solves, who it affects, effort against value, dependencies, risk and what AI makes cheap to build that was not before
- Turn the agreed priorities into a program plan sequenced across the Workflow Automation and DevOps teams so builds do not compete for the same people
- Keep the backlog honest: retire items that no longer earn their place and surface new demand as it arises, including opportunities the teams' own AI tooling opens up and controls or process changes the compliance program needs built
Discover and design with SMEs, AI first
- Run discovery with the SMEs who own the process: current state, pain points, target state, constraints and what success will look like, using AI to capture, structure and play back what they tell you
- Map the process and write the requirements so the team can build without re-discovery: user stories, data requirements, non functional requirements and acceptance criteria, drafted with AI, tested against the SMEs and refined until they are right
- Facilitate design sessions between SMEs and engineers, and use AI to prototype, mock and pressure test options in the room rather than in the next sprint
- Agree scope, plan, milestones and resourcing for each build before work starts
Deliver through the SSDLC with AI native teams
- Run agile delivery for the Workflow Automation and DevOps teams with their leads, following Triskele Labs' SSDLC: planning, stand ups, reviews, retros, security gates and release readiness
- Understand how the teams build with AI, what makes them faster or slower, and shape the program around that rather than around a traditional engineering cadence
- Clear the path ahead of the teams: decisions made, SMEs available, dependencies resolved and acceptance criteria agreed before they become blockers
- Manage scope, change and dependencies across the five concurrent builds and keep the CTO and SMEs informed of progress, blockers and trade offs
- Plan and coordinate testing with the DevOps team, within the SSDLC: acceptance criteria agreed up front, AI generated test cases reviewed and run, UAT with the SMEs, defects triaged and closed
- Own implementation and go live: documentation (AI drafted, human checked), training, cutover, communication and a named owner for every tool and automation shipped
- Close each build with a review of what was delivered against what was scoped and how much faster it could have gone, and carry the lessons into the next one
Govern, measure and accelerate
- Establish light, fit for purpose program governance (templates, stage gates, RAID log, reporting cadence) aligned to the SSDLC, built with AI and designed to speed delivery up rather than add steps in front of it
- Produce one internal program report on a regular cadence, generated from live delivery data, with status, risk and delivery metrics that the CTO and ELT use to make decisions
- Build and analyse the data behind delivery: dashboards, cycle time and throughput, trend and variance reporting, adoption after go live, and how much of each build AI carried
- Keep current on what AI and modern engineering practice make possible, trial new tooling and ways of working, and bring what works into the program and the teams
- Mentor a Graduate Project Manager on planning method, AI assisted ways of working and stakeholder management, and bring their projects into the program view where they touch the build teams
Requirements
What we are looking for
Someone who already works AI first. The Technical Program Manager uses AI as the default way of gathering information, doing analysis, writing requirements, planning, making updates, drafting documentation and reporting, and treats a task done without it as the exception that needs a reason. They understand how engineering teams that build primarily with AI actually work, can hold a credible technical conversation with them, and are always looking for the next thing that will make them faster.
This is a multi-faceted role. Strong business analysis underpins all of it: a program manager who cannot analyse a process, write requirements an engineer can build from and read delivery data critically will not succeed in it.
Essential
- Demonstrated AI competency: uses AI tooling daily and expertly in their own work (analysis, requirements, documentation, test planning, reporting) and has worked with, or can credibly engage with, engineering teams that build primarily with AI
- 3 or more years in technical program, project or delivery management
- Demonstrated business analysis capability: requirements elicitation and documentation, user stories and acceptance criteria, options analysis, and the judgement to know when a problem needs a process fix rather than a tool
- Strong analytical and data skills: comfortable building and interpreting dashboards, cycle time and throughput metrics, trend and variance analysis and adoption tracking; able to interrogate data rather than take it at face value
- Technically fluent: able to hold a conversation about architecture, environments, integration, security controls and AI tooling with engineers without translation
- Experience shaping and prioritising a tooling, product or automation backlog with a technical executive, and articulating value, effort, dependency and risk trade offs clearly
- Experience running the full agile delivery lifecycle with software, platform or automation teams inside a defined secure development lifecycle: discovery and planning with SMEs, design, delivery, testing and UAT, implementation and handover to operation
- Proven ability to run concurrent builds with different stakeholders, switch between strategic and detailed work in the same day, and keep each on schedule
- Clear written and verbal communication across the full range, from engineering detail to a one-page ELT summary
- Influence without authority: a track record of getting commitments and decisions from peers and senior people who do not report to you
- A bias to removing friction: comfortable in a lean, fast moving business where governance must be proportionate, templates are built rather than inherited, and the role shapes its own operating model
Desirable
- Hands on experience with agentic AI tooling, AI coding assistants or workflow automation platforms (for example n8n, Power Automate or similar), and a view on what is cheap and expensive to automate
- Experience with DevOps or platform engineering teams: CI/CD, release management, environments, and the difference between a prototype and a supportable internal tool
- Background in cybersecurity, managed services or another operationally intensive technology business where internal tooling directly affects service delivery
- Experience mentoring or developing junior project staff
- Change management experience: communication planning, training design, adoption measurement and sustaining change after go live
- Formal qualifications in project management (PRINCE2, PMP, MSP), business analysis (BABOK or IIBA) or agile delivery (Scrum, SAFe)
- Experience selecting and administering project portfolio tooling (for example Asana or Jira) and building automated reporting from it
Benefits
- A new and strategic role with autonomy to shape what you build.
- This is an AI-native role.
- A high-trust, high-accountability culture and direct exposure to executive leadership.
- Competitive salary
- Investment in training, certification, and conference attendance.
- Hybrid working out of our Melbourne office.
- Access to Triskele Labs Benefits Program
How to Apply
Applicants should provide a CV and a short cover note addressing the essential criteria, including how they use AI in their own work today. Shortlisted candidates will complete a practical exercise using whatever AI tooling they choose: analyse a short process description, identify the tooling or automation opportunity, and produce a one page plan covering scope, requirements an engineering team could build from, delivery approach under an SSDLC, and how it would be tested and implemented. We will ask how it was produced as well as what it says.
Triskele Labs is an equal opportunity employer. Applicants must have the right to work in Australia; some projects may require the ability to obtain an Australian Government security clearance.