Required Skills & Experience

AWS & Agentic AI

- Strong experience with AWS cloud services and modern AI platforms.
- Hands-on experience with:
- Amazon Bedrock
- Bedrock Agents
- AWS AgentCore
- Anthropic Claude Models on Amazon Bedrock
- Claude Code
- Experience building production-ready Agentic AI and Generative AI solutions.

AI Engineering & LLMs

- Strong understanding of:
- Large Language Models (LLMs)
- Agentic delivery of the Software Development Lifecycle
- Automated Testing
- GitHub
- AI Guardrails and Responsible AI
- Experience working with:
- Anthropic Claude Code
- Experience in model evaluation, model routing, model orchestration, and weighted AI model selection strategies based on performance, latency, and cost optimization.

Development & Agent Frameworks

- Strong programming experience in:
- Python
- REST APIs
- Microservices Architecture
- Hands-on experience with:
- Claude Code
- Experience developing:
- Autonomous AI Agents
- Multi-Agent Systems
- AI Assistants
- AI Workflow Automation Platforms

AWS Cloud Services

Experience with:

- AWS Lambda
- API Gateway
- DynamoDB
- S3
- IAM
- CloudWatch

DevOps & Platform Engineering

- Experience with CI/CD pipelines.
- Infrastructure as Code
- Source control
- Claude Code
- AI observability, monitoring, evaluation, and governance frameworks.

Preferred Qualifications





- AWS Certified AI Practitioner.
- AWS Certified Machine Learning Specialty.
- AWS Certified Solutions Architect Associate or Professional.
- Experience delivering enterprise-scale GenAI and Agentic AI programs.
- Experience building AI applications on Amazon Bedrock.
- Experience implementing AI coding assistants such as Claude Code and Amazon Q Developer.
- Experience with regulated industries such as Financial Services, Healthcare, Telecommunications, Government, or Public Sector.

Soft Skills

- Strong stakeholder engagement and consulting skills.
- Excellent communication and presentation capabilities.
- Ability to convert business requirements into innovative AI solutions.
- Solid analytical and problem-solving mindset.
- Ability to work effectively across cross-functional teams.
- Passion for emerging AI technologies and continuous learning.

Success Measures

- Successful delivery of production-grade Agentic AI solutions.
- Increased automation through intelligent AI agents.
- Improved operational efficiency and business outcomes.
- Adoption of AI best practices, governance, and security standards.
- Scalable, secure, and measurable AI platforms deployed across enterprise environments.

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📌 AWS AI Engineer (Sydney)
🏢 BULLIT MANAGEMENT SERVICES
📍 Sydney