Ai tech lead

• Lead technical design decisions and resolve blockers across portfolio use cases
• Drive cloud-native development practices, including secure handling of secrets, environment variables, and service configurations
• Manage API specifications and service integrations across platforms
• Ensure robust CI/CD pipelines for AI systems and microservices
• Implement team-based access control, code ownership, and repository governance
• Apply infrastructure-as-code practices for scalable deployments
• Support agile software development processes and ensure engineering consistency
• Design and deploy conversational agents and multi-agent systems
• Orchestrate agent workflows, manage context, and integrate external data sources
• Implement retrieval-augmented generation (RAG) patterns and scalable inference strategies
• Evaluate trade-offs between deployment models (e.g., serverless vs containerised) for optimal performance
• Ensure compliance with enterprise data privacy and cybersecurity standards
• Manage responsible handling of user interactions and logs, with clear boundaries for data retention and observability
• Implement observability tools for tracing, logging, and performance monitoring
• Ensure robust API testing and authentication flows across service layers
• Manage code reviews, shared modules, and enforce engineering best practices
• Drive agile development practices including sprint planning, backlog grooming, and velocity tracking
• Foster a growth mindset culture, encouraging experimentation, learning from failure, and continuous improvement
• Support onboarding and mentoring of developers and AI engineers
• Work closely with the AI Tech Chapter Lead to align technical decisions with AI platform strategy and business goals
• Represent the Pod in technical forums, showcases, and architecture reviews
• Communicate risks, trade-offs, and technical constraints clearly to non-technical stakeholders
• Provide timely updates to the Engagement Lead on technical decisions and progress

• Bachelor’s degree in Computer Science, Engineering, or related field
• 6+ years of experience in AI/ML engineering, with strong expertise in Generative AI and agentic systems
• Proficiency in Python and modern programming languages
• experience with orchestration frameworks (LangChain, Hugging Face, OpenAI)
• Strong knowledge of cloud platforms (AWS, Azure), containerisation (Docker, Kubernetes), and CI/CD pipelines
• Experience with infrastructure-as-code (Terraform, CloudFormation) and API management
• Familiarity with observability tools and secure coding practices
• Excellent leadership, stakeholder engagement, and communication skills
• Proven ability to lead technical teams and deliver complex AI solutions in agile environments

If you think you can do this job but don’t meet all the criteria, that’s OK! Please apply. At Woodside, we value people with diverse experiences and backgrounds

• Commitment to your ongoing development, including on the job opportunities and formal programs
• Inclusive parental leave entitlements for both parents
• Values led culture
• Flexible work options
• Generous annual leave, sick leave and casual leave
• Cultural and religious leave with flexible public holiday opportunities
• A competitive remuneration package featuring performance based incentives with uncapped Employer Provident Fund