Sr. AI Engineer
About The Position
The Senior AI Engineer is responsible for designing and delivering scalable full-stack AI systems, with ownership of both backend agent architecture and frontend application performance. This role focuses on system design, performance optimization, establishing best practices across agent development and data workflows, and testing, ensuring AI capabilities are delivered through intuitive and reliable user experiences. The Senior AI Engineer also mentors junior team members and plays a key role in improving system reliability, scalability, maintainability, and the robustness of AI agents.
Requirements
- 5–7 years of experience
- Proven experience building full-stack AI systems
- Strong proficiency in TypeScript and Python
- Strong experience with React architecture and modern frontend patterns
- Deep understanding of LLM systems, RAG, and agent orchestration frameworks (e.g. LangGraph)
- Experience designing distributed and containerized systems
- Strong experience with AWS and Azure architecture, including multi-service integration
- Experience with DynamoDB and scalable storage patterns
- Strong experience with Databricks for analytics, monitoring, and optimization
- Familiarity with AI agent testing frameworks (such as DsPy or equivalent tools) and experience with red-teaming methodologies
- Advanced debugging, troubleshooting, and performance optimization skills
- Ability to define best practices for full-stack development and frontend-backend integration
Responsibilities
- Design, implement, and maintain scalable AI agent architectures
- Own and optimize RAG pipelines, including indexing and retrieval strategies
- Architect and enhance Lambda-based data processing and indexing workflows
- Design and improve React application architecture and state management
- Ensure seamless integration between frontend interfaces and backend AI systems
- Optimize user experience for AI-driven applications (latency, streaming, feedback loops)
- Improve CI/CD pipelines and deployment processes across environments
- Develop and execute AI agent testing strategies, including functionality tests, performance evaluation, and contributing to red-teaming exercises
- Use DsPy or equivalent tools and methods to evaluate and improve AI agent performance
- Analyze system performance using DataDog and Databricks; implement improvements
- Mentor junior engineers and conduct code reviews across full-stack components
- Contribute to technical standards, development best practices, and agent evaluation guidelines
Benefits
- Competitive pay
- Excellent benefits
- Great culture rooted in our core values
- Opportunities for career development
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed
