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Tech Stack
Tools & technologiesAWSDistributed SystemsDynamoDBJavaPythonSpringTerraformTypeScript
About the role
Key responsibilities & impact- Champion a specification-first approach to AI development
- Build production-grade LLM and agentic AI applications using Spring AI
- Architect and operate AWS AI infrastructure alongside core AWS services
- Communicate technical concepts clearly to both technical and non-technical stakeholders
- Mentor engineers and conduct thorough code reviews
Requirements
What you’ll need- Deep expertise in the AI software development lifecycle with a specification-first mindset
- Experience authoring AI feature specs (acceptance criteria, evaluation metrics, prompt contracts)
- Track record of shipping AI-powered features through multiple product cycles with engineering rigor
- Strong hands-on experience with Amazon Bedrock, Bedrock Agents, Agent Core, SageMaker, and Amazon Q
- Solid knowledge of core AWS infrastructure (ECS/EKS, Lambda, RDS, DynamoDB)
- Experience architecting AI infrastructure pipelines
- Hands-on experience building production applications with Spring AI
- Java, TypeScript & Python with 5+ years of professional software engineering
- Experience designing and operating distributed systems at scale
- Proficiency in CI/CD pipelines, Infrastructure as Code (Terraform, CloudFormation)
Benefits
Comp & perks- Competitive salary
- Flexible working hours
- Professional development opportunities
- Remote work options
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
AI software development lifecyclespecification-first approachAI feature specsAmazon BedrockSageMakerJavaTypeScriptPythonCI/CD pipelinesInfrastructure as Code
Soft Skills
communicationmentoringcode reviews
