Product Owner - AI Powered Engineering at Commonwealth Bank
Sydney, New South Wales, Australia -
Full Time


Start Date

Immediate

Expiry Date

28 Nov, 25

Salary

0.0

Posted On

28 Aug, 25

Experience

0 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

No

Skills

Good communication skills

Industry

Electrical/Electronic Manufacturing

Description

TECHNICAL PRODUCT OWNER | AI POWERED ENGINEERING

  • Fuel your passion for AI and Engineering and transform outcomes
  • Join Australia’s largest bank as we lead the world in AI innovation and ambition!
  • Let’s r evolutionise our engineering community with cutting-edge AI tools and capabilities!
Responsibilities
  • Lead a cross-functional squad with an Engineering Lead to deliver an AI-powered engineering product suite (e.g., code assistants, test-generation, documentation automation, incident copilots), providing clear delivery plans, measurable outcomes, and transparent reporting.
  • Own and execute the product roadmap— prioritising backlog items, defining OKRs, and orchestrating discovery, experimentation, and incremental releases with a strong focus on value realisation .
  • Partner with engineering squads, AI researchers, platform teams, and risk/compliance to assess use cases, pilot tools, validate hypotheses, and scale proven capabilities across the Bank.
  • Translate customer and developer needs into actionable requirements and acceptance criteria; ensure robust telemetry, feedback loops, and continuous improvement.
  • Navigate a complex enterprise environment—aligning stakeholders, resolving cross-team dependencies, and managing risks, controls, and regulatory considerations associated with AI use in software engineering.
  • Facilitate agile ceremonies (stand-ups, planning, reviews, retros), remove blockers, optimise flow, and improve delivery predictability and velocity.
  • Establish product health metrics (adoption, utilisation , quality, cycle time, DORA metrics uplift) and socialise outcomes through executive-ready updates and storytelling.
  • Maintain currency on AI advancements (e.g., LLMs, retrieval-augmented generation, agents, evaluation frameworks) and work with engineering to apply them pragmatically to solve real developer experience and productivity challenges.
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