2 months ago
Melbourne, AustraliaStaff+
Responsibilities
- Own AI solution delivery from problem framing and feasibility assessment through architecture, implementation, production release and continuous improvement.
- Design enterprise architectures integrating AI capabilities with applications, APIs, data platforms, identity, security and operational controls.
- Build or review critical software components and establish coding, testing, quality, cost and maintainability standards.
- Design and implement agentic applications using retrieval-augmented generation, MCP, function/tool calling, structured outputs and multi-agent workflows.
- Engineer production AI platforms covering inference architectures, model routing, caching, semantic retrieval, vector databases, evaluation pipelines, observability and cost optimization.
- Define evaluation criteria, test sets, feedback loops and monitoring for accuracy, reliability, safety, latency, cost and business impact.
- Implement responsible AI guardrails, human oversight, access controls and auditability with security, privacy, risk and legal partners.
- Collaborate with product owners, business leaders, architects, data specialists and delivery teams to create achievable roadmaps.
- Mentor engineers, contribute reusable patterns and reference implementations, and communicate technical recommendations to technical and non-technical stakeholders.
Requirements
- Typically 10-12 years of professional experience in software engineering, solution architecture, platform engineering or related enterprise technology roles.
- Demonstrated experience designing and delivering production enterprise applications, integrations or digital platforms in complex, regulated or security-conscious environments.
- Recent hands-on experience implementing AI-enabled solutions such as agentic applications, retrieval-augmented generation, intelligent workflow automation or machine-learning services.
- Strong software engineering fundamentals including API design, distributed systems, automated testing, version control, observability and secure development practices.
- Proficiency in Python and practical experience with at least one enterprise application stack such as Java, .NET or TypeScript/Node.js.
- Experience delivering on at least one major cloud platform, including AWS, Microsoft Azure or Google Cloud.
- Working knowledge of enterprise data integration, SQL, search/retrieval, and structured and unstructured information.
- Understanding of model and application evaluation, prompt and context design, privacy, security, responsible AI controls and production monitoring.
- Experience leading technical work across multidisciplinary teams, mentoring engineers and influencing architecture or engineering standards.
- Strong communication, commercial judgment and ability to translate ambiguous business needs into feasible technical approaches and delivery plans.
- A degree in computer science, engineering or a related discipline, or equivalent professional experience.
- Consulting, professional services or client-facing technology delivery experience is useful but not essential.
- Regulated-industry or enterprise risk, compliance and governance experience is useful but not essential.
- Familiarity with AI application frameworks such as Langraph or PydanticAI and model platforms such as Azure Foundry or AWS Bedrock is useful but not essential.
- Experience operating containerized workloads or collaborating with platform teams using Kubernetes and infrastructure as code is useful but not essential.
Benefits
- Hybrid work arrangement with remote flexibility and at least three days per week in the local office or onsite with clients.
- Office-based teams identify at least one weekly anchor day for in-person collaboration.
- Applicants must have appropriate approval to work in Australia.
- Successful applicants must complete a Criminal & Bankruptcy check before employment begins.
- Inclusive and flexible work environment with diversity and professional development support.
Tech Stack
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