Agiloft is seeking a Fullstack Developer - Agentic AI to lead the design, development, and delivery of next-generation applications on their award-winning CLM platform, focusing on building and extending agentic AI platforms and services.
Requirements
- Proven experience in building agentic AI platforms/services
- Strong expertise in AWS cloud services, including microservices, containers (Docker, ECS, EKS), serverless (Lambda), and data services.
- Proficiency in modern programming languages (e.g., Python, Java, TypeScript/JavaScript).
- Experience with front-end frameworks such as React or Vue.js.
- Strong knowledge of databases (SQL and NoSQL)
- Familiarity with DevOps practices, CI/CD pipelines, infrastructure as code (Terraform/CloudFormation).
- Experience with the development of agentic AI services, including MCP servers.
Responsibilities
- Lead the design and development of complex full-stack applications, ensuring scalability, reliability, and maintainability.
- Refine and implement software architecture patterns for agentic AI platforms and microservice-based systems.
- Drive best practices for code quality, performance, security, and cloud-native design.
- Build, test, and deploy agentic AI services that leverage and orchestrate MCP services on Agiloft’s CLM platform as well as on 3rd-party platforms.
- Design and implement microservices on AWS based on Agiloft’s policies and design pattern and industry best-practices.
- Develop high-performance APIs and integrations for internal and external systems.
- Write clean, maintainable, and testable code across the stack (front-end, back-end, databases, infrastructure).
Other
- 7+ years of professional software development experience, with significant exposure to full-stack engineering.
- Excellent problem-solving, communication, and leadership skills.
- Experienced at working in a globally distributed team in a remote-only environment.
- Prior leadership experience in guiding engineering teams and influencing architectural decisions.
- Contributions to open-source projects or published work in AI systems engineering.
