Full stack AI Engineer
Expired
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Virtusa
Sydney NSW
Full Time
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Posted 6 months ago
This role is expired
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View all AI roles →Manager - AI Governance and Enablement
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- Lead enterprise-wide AI governance, strategy and delivery
- Proven experience in AI governance frameworks and policy
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- PhD with 3+ years or Master's with 7+ years in data science/engineering
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Data & AI Capability Lead
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Adelaide, SA | Brisbane, QLD | Canberra, ACT | Hobart, TAS | Melbourne, VIC | Sydney, NSW
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Posted 5d ago
JD:
Technical Skills
- Frontend: React, TypeScript, Next.js, design systems (e.g. Figma-based, token-driven)
- Backend: Python, Node.js, Java, .NET Core, C#
- Databases: SQL, NoSQL (Postgres, MongoDB)
- Data Technologies: AWS-native tools (DynamoDB, Aurora, S3, Glue, Athena, Redshift)
- Architecture: Microservices, event-driven systems, distributed design
- Cloud: AWS (e.g. Certified Developer/Architect), Azure
- DevOps: GitHub Actions, Jenkins
- Containers: Docker, Kubernetes
- Security: Secure-by-design systems, threat modelling
- Testing: Unit, regression, contract testing, CI/CD automation
- Observability: Prometheus, Grafana, OpenTelemetry (if relevant)
AI & Emerging Technology
- Understand how AI and machine learning can enhance software engineering workflows and productivity
- Have experience or interest in building AI-assisted engineering tools or AI-integrated applications (e.g., using LangChain, LlamaIndex, or GenAI APIs)
- Use AI-powered coding assistants like GitHub Copilot, Cursor, Continue, or Aider in day-to-day development
- Are curious about agentic systems and AI experimentation in real-world product environments
JD:
Technical Skills
- Frontend: React, TypeScript, Next.js, design systems (e.g. Figma-based, token-driven)
- Backend: Python, Node.js, Java, .NET Core, C#
- Databases: SQL, NoSQL (Postgres, MongoDB)
- Data Technologies: AWS-native tools (DynamoDB, Aurora, S3, Glue, Athena, Redshift)
- Architecture: Microservices, event-driven systems, distributed design
- Cloud: AWS (e.g. Certified Developer/Architect), Azure
- DevOps: GitHub Actions, Jenkins
- Containers: Docker, Kubernetes
- Security: Secure-by-design systems, threat modelling
- Testing: Unit, regression, contract testing, CI/CD automation
- Observability: Prometheus, Grafana, OpenTelemetry (if relevant)
AI & Emerging Technology
- Understand how AI and machine learning can enhance software engineering workflows and productivity
- Have experience or interest in building AI-assisted engineering tools or AI-integrated applications (e.g., using LangChain, LlamaIndex, or GenAI APIs)
- Use AI-powered coding assistants like GitHub Copilot, Cursor, Continue, or Aider in day-to-day development
- Are curious about agentic systems and AI experimentation in real-world product environments