About the role
from listingBuild secure AI applications from concept to production using large language models and advanced analytics.
Help shape how intelligent technology delivers real outcomes across the business. You will turn challenging problems into secure, scalable applications powered by artificial intelligence and advanced analytics. You will partner with experts across product, data, engineering, and governance to deliver solutions that matter. If you enjoy moving from concept to production and driving measurable impact, you will thrive here.
As an AI Applications Developer in the Intelligent applications team, you will design, build, and deliver production-grade solutions that apply model-driven capabilities to real business needs. You will partner with cross-functional teams to move from discovery through launch, with a focus on security, scalability, and responsible use. You will help improve reliability through systematic evaluation, monitoring, and iterative enhancement. You will contribute to shared patterns, documentation, and engineering practices that enable reuse and supportability.
Job responsibilities
Design and deliver production-grade applications powered by large language models and advanced analytics
Build agent-based systems that plan, decompose, and execute complex workflows across tools and services
Develop and optimize prompts, evaluation methods, and guardrails to improve reliability and user outcomes
Implement retrieval-augmented generation patterns to ground model outputs in trusted data sources
Integrate applications with cloud services, data stores, and APIs to support end-to-end workflows
Partner with product, data, engineering, and governance stakeholders to define requirements and deliver solutions
Apply secure-by-design practices, including access controls, data protection, and auditability throughout development
Create automated tests, monitoring, and observability to improve quality, safety, and operability in production
Document architectures, decisions, and runbooks to enable supportability and reuse across teams
Troubleshoot performance, latency, and model quality issues and deliver iterative improvements
Stay current on advances in generative and agent-based approaches and translate them into practical solutions
Required qualifications, capabilities and skills
Professional experience building and deploying modern applications in a production environment
Hands-on Python development experience, including writing maintainable, testable code
Demonstrated experience building intelligent applications using large language models, including prompt design and systematic evaluation
Demonstrated experience implementing agent frameworks (for example, Google Agent Development Kit or similar)
Demonstrated experience with retrieval-augmented generation solutions, including indexing, retrieval strategies, grounding, and citations
Hands-on experience with containerized development and deployment (for example, Docker and orchestration platforms)
Hands-on experience with cloud services for data and application workloads (for example, managed compute, storage, databases, and serverless services)
Strong understanding of secure development practices, including identity and access controls and data handling principles
Ability to translate ambiguous business problems into technical designs, milestones, and measurable outcomes
Strong analytical and problem-solving skills, including root-cause analysis in production systems
Preferred qualifications, capabilities and skills
Experience deploying and operating solutions on Kubernetes (for example, Amazon Elastic Kubernetes Service)
Experience with managed model platforms and orchestration patterns (for example, Amazon Bedrock or similar)
Experience building data pipelines and analytics workflows (for example, AWS Glue and Amazon Athena)
Experience with relational database design and performance tuning (for example, Amazon Relational Database Service)
Experience implementing model fine-tuning or adaptation techniques with clear evaluation and governance practices
Experience partnering with risk, controls, privacy, and compliance stakeholders on model-enabled products
Experience mentoring engineers and establishing team development standards and reusable patterns