Resonate is looking to transform its SaaS platform into a fully agentic system by building the core infrastructure for a new class of intelligent tools that move beyond simple automation, solving novel engineering challenges inherent in AI-native applications.
Requirements
- Expert-level proficiency with Java/Spring Boot backend development and React/TypeScript frontend development
- Demonstrated expertise in designing, deploying, and managing cloud-native applications on AWS.
- Proven experience integrating AI/ML models and third-party APIs into a production software environment.
- Strong architectural skills and a deep understanding of distributed systems, microservice patterns, and event-driven design.
- Proficiency with relational databases and SQL.
- Experience with vector databases or search services is highly desirable.
- Experience with Generative AI technologies such as OpenAI, LangChain, and Amazon Bedrock
Responsibilities
- Build the architecture and development of scalable, resilient backend microservices and deploy them within our AWS infrastructure.
- Build and enhance our user-facing platform with modern React, TypeScript, and Next.js creatingNext.js creating intuitive interfaces that seamlessly integrate complex, AI-driven features.
- Design and implement the core technical infrastructure to support our AI agents, including API gateways, state management systems for agentic workflows, and observability into AI operations.
- Integrate and orchestrate various LLM models and services to connect our AI's reasoning to our backend systems and data stores.
- Develop and optimize data architectures using relational and vector databases to provide our agents with fast, relevant context for memory and RAG.
- Leverage a suite of AWS services to build, deploy, and monitor our AI-native applications.
- Apply engineering best practices and processes to support the technical vision for the platform.
Other
- 7+ years of professional software engineering experience, with a strong portfolio of building and scaling SaaS applications
- A pragmatic approach to engineering, with a solid understanding of the trade-offs between performance, cost, and scalability in AI systems.
- A passion for mentoring and elevating the skills of the entire engineering team.
- Ownership: You take initiative, follow through, and hold yourself accountable.
- Collaboration: You value working with others and building strong, respectful relationships.
