Mark Davidson · Melbourne, Australia

I build agentic AI systems that hold up in production.

Principal AI Solutions Engineering Lead, APAC at Atlassian. I design and ship agentic AI and LLM systems in Python, working with the top 1% of Atlassian's enterprise accounts across Asia-Pacific.

Portrait of Mark Davidson

Organisations I’ve worked with

  • Canva
  • Westpac
  • Telstra
  • REA Group
  • Qantas
  • Coles
  • Transport for NSW
  • Domino's
  • Lendi Group

In production

AI systems I’ve built, shipped and run.

In production

Demo-personalisation pipeline

Turns Salesforce opportunity context and public company signals into tailored demo environments. Atlassian Solutions Engineers run it globally, and it built the demo environments for Atlassian’s Team ’26 conference, including one the CEO presented live.

runs globally
3,000+
hours saved
10,000+
less prep time
~97%
  • Python
  • RAG
  • Salesforce

Built & operated

Sales AI Reporting Hub

A multi-agent platform I conceived, built and now operate. Each week it analyses the open sales pipeline and writes a risk review of the largest cloud migration deals.

agents
7
opportunities a week
900+
fields per deal
30+
  • Python
  • Salesforce API
  • Atlassian AI Gateway
  • Workato

Back tested

At-risk deal detector

Checks every open opportunity in the quarter against 5 years of Salesforce opportunity history and public market indicators, then flags the deals at risk. Back tested against past deal outcomes.

of deal history
5 yrs
  • RAG
  • ChromaDB
  • BGE embeddings

Shipped

Provisioning MCP server

Exposes Atlassian site and organisation admin APIs as tools for autonomous agents, so tailored demo environments are provisioned end to end without manual setup.

  • Python
  • Model Context Protocol
  • Atlassian admin APIs

How I test before release

  • Known-answer test sets
  • Rubric-based grading of sampled outputs
  • Back testing against past outcomes

Also built: the Williams Racing Briefing Agent, a RAG system that writes a one-page brief for executives hosting customers.

What I do

Between architect and engineer: close to the customer, and close to the code.

  1. Build & operate

    Production AI in Python, shipped end to end and run after launch, not just the deck.

    • RAG pipelines and multi-agent systems
    • MCP servers and tool calling
    • Prompt and context engineering
  2. Architect

    Solution architecture for enterprise AI, with the security and governance answers needed to get it approved.

    • Technical discovery and proofs of concept
    • Architecture, security and governance advisory
    • OAuth, SSO, SCIM and enterprise integration
  3. Enable

    Hands-on work with engineering teams, so they can run what we build together.

    • Workshops and code reviews
    • Enablement on AI-assisted coding and agents
    • Member of Atlassian’s AI Council

About

Most of my work happens alongside customer teams.

I’m a Principal AI Solutions Engineering Lead at Atlassian, based in Melbourne. I have 8+ years in enterprise delivery, and I’ve spent the last 2+ years building production AI in Python.

I embed with engineering teams at Atlassian’s largest customers. We work out what AI can usefully do in their environment, design it end to end, and build enough of it together to know it works. I run hands-on workshops and code reviews, and answer the architecture, security and governance questions that decide whether it ships.

The role sits between architect and engineer. I’ve found the work goes better when those two jobs aren’t separated by a wall.

Recognition & community

  • SE Rockstar of the Quarter (APAC), Atlassian
  • Raised $25,000 for Kids Under Cover
  • Pro-bono consulting for Lifeline and WWF

Experience

8+ years from consulting and fintech to production AI.

  1. Principal AI Solutions Engineering Lead, APAC

    Atlassian

    Aug 2025 – Present

    Technical lead on agentic AI and production LLM systems, including Atlassian Rovo, for the top 1% of enterprise accounts across APAC. Called in on the region's largest AI opportunities to resolve C-level architecture, security and governance concerns, and tie them to measurable outcomes.

    • Built and operate the demo-personalisation pipeline, the Sales AI Reporting Hub and a provisioning MCP server.
    • Embed with customer engineering teams: hands-on workshops, code reviews, and AI implementations from concept to production.
    • Serve on Atlassian’s AI Council. Wrote the Rovo Dev CLI reference guide and a white paper on secure, AI-ready content management.
  2. Senior Enterprise Solutions Engineer

    Atlassian

    Jan 2022 – Aug 2025

    Technical lead on strategic and enterprise accounts. Shaped solution architecture through executive workshops, proofs of concept and technical validations, and took complex transformation deals from discovery to close.

    • $110M+ in annual contract value closed as technical lead, including the largest APAC Cloud deal at closure: $25M total contract value, since expanded to 46,000 users.
    • Led technical strategy on a stalled 45,000-user cloud migration for a Big Four bank, through to its September 2024 production launch.
    • Built early internal AI agents on Salesforce data and showed multi-agent orchestration patterns to Solutions Engineers globally.
  3. Senior Solutions Architect

    Data Action (Financial Services Technology)

    Jun 2021 – Jan 2022

    Technical lead for enterprise banking clients of a fintech processing $403M in transactions a month.

    • Technical lead on 2 banking service contracts worth $9.5M+ a year.
  4. Senior Solution Architect

    GLiNTECH (Atlassian Platinum Solution Partner)

    Aug 2019 – Jun 2021

    Client-facing architect on cloud migrations, process re-engineering and end-to-end delivery for private and public sector clients.

    • 30,000+ end users reached through 38+ solutions across 18 projects.
    • $21M across 6 deals secured, and up to $120K a month saved for clients through automation and integration.
  5. Technology Operations Manager

    KPMG (Banking & Financial Services Consulting)

    Feb 2018 – Aug 2019

    Led technical operations for a $60M Big Four financial remediation program with a risk and compliance focus.

    • Cut key processing times from 5 days to 3, and manual workload by 15%, through end-to-end automation.

Education & certifications

Computer science, AI strategy and delivery.

  • Bachelor of Computer Science

    Swinburne University of Technology

  • Building an AI Strategy

    AGSM at UNSW Sydney (Executive Short Course)

  • Certified SAFe 6 Practitioner

    Scaled Agile, 2024

  • Lean Six Sigma Green Belt

    APMG International

  • Certified ScrumMaster

    Scrum Alliance

Contact

Have something worth building?

Whether it’s a role, a project or a production AI problem, I’d like to hear about it. Hiring? I’m happy to share my CV.