7 hours ago
Auckland, New ZealandSenior
Responsibilities
- Build technical relationships with customers and serve as a trusted advisor for GenAI, ML, and agentic technology adoption.
- Design scalable, secure, resilient, and cloud-native AI architectures for customer use cases.
- Recommend improvements for security, cost, performance, reliability, and operational efficiency.
- Implement or advise on RAG, LLM and multimodal foundation model integration, fine-tuning, distributed inference, evaluation, vector databases, agentic workflows, prompt engineering, and MLOps.
- Capture customer needs and influence the roadmap for AWS GenAI, ML, and agentic features.
- Create and share best practices, reference architectures, code samples, whitepapers, blog posts, workshops, and other technical content.
- Lead hands-on technical deep dives and workshops while contributing reusable code and technical assets.
- Provide technical leadership and mentorship to the broader engineering organization.
Requirements
- 7+ years of experience in application and infrastructure design, implementation, or consulting.
- 5+ years of experience in relevant technology domains such as software development, cloud computing, systems engineering, infrastructure, security, networking, or data and analytics.
- 6+ years of experience designing and implementing production AI systems.
- 5+ years managing technical, customer-facing resources.
- Hands-on experience with AWS ecosystems, including Bedrock, AgentCore, and SageMaker, for secure private-network AI environments.
- Practical experience implementing Retrieval-Augmented Generation using embeddings, vector stores, and semantic search optimization.
- Experience integrating LLMs and multimodal foundation models into large-scale systems, including fine-tuning, deployment, distributed inference, RAG, foundation model evaluation, vector databases, agentic workflows, prompt and context engineering, and MLOps.
- Ability to influence customer and internal business decision-makers as a technical thought leader and communicate effectively with diverse audiences.
- Preferred: cloud technology certification such as Solutions Architecture, Cloud Security Professional, or Cloud DevOps Engineering.
- Preferred: experience leading teams or organization-wide initiatives with partially defined business objectives.
- Preferred: experience leading complex projects toward extensible, operationally excellent, cost-optimized solutions.
- Preferred: technical cloud certification and a master's degree in computer science, mathematics, statistics, machine learning, or an equivalent quantitative field, or a PhD.
- Preferred: experience running and fine-tuning large and small language models using LoRA, QLoRA, Instruction Tuning, and RLHF.
- Preferred: experience architecting AI systems in regulated or security-sensitive environments such as financial services, healthcare, or the public sector.
Tech Stack
Categories
Solutions Engineering
About Amazon
Amazon builds and operates a global e-commerce marketplace, logistics network, and consumer devices, and provides cloud computing via AWS for businesses and developers. The company earns revenue from online retail, third‑party seller services, subscriptions like Prime, advertising, and AWS usage. Founded in 1994 and headquartered in Seattle, it is publicly traded on NASDAQ (AMZN) and serves customers in dozens of countries.