Transforming a manual content review process into a streamlined, self-service solution using Generative AI by automating the review of resumes, presentations, and books through AI classification and release rules to cut down review time and increase efficiency.
Requirements
- Strong Python application development skills with experience in modern frameworks (FastAPI preferred; Flask, Django acceptable)
- Experience designing and implementing scalable, maintainable, and OOP-based software in distributed systems
- Curiosity in LLM prompt engineering, context engineering, or agentic applications
- Proficiency with source control (Git) and CI/CD pipelines (AWS CodeBuild preferred, Jenkins, GitLab CI, GitHub Actions)
- Familiarity with DevSecOps practices, containerization (Docker, Kubernetes), and cloud infrastructure
- Experience with testing frameworks (PyTest preferred; unittest acceptable)
- Experience with Python project and dependency management tools (poetry preferred; uv, make, pip, conda acceptable)
Responsibilities
- Design, implement, and maintain scalable backend services and APIs in a containerized cloud environment (AWS preferred)
- Build mission-critical production applications focused on data discovery, analysis, and secure data delivery
- Integrate with cloud services and data platforms to expose high-value data through secure, performant interfaces
- Contribute to application features that integrate LLMs, agents, or ML models into production systems
- Collaborate in a Lean Agile environment with teammates and stakeholders, participating in code reviews, system design, and continuous improvement
- Work with CI/CD pipelines, modern build tools, and testing frameworks to ensure quality, security, and delivery speed
- Monitor and improve the performance and reliability of services, APIs, and data-driven components
Other
- Active TS/SCI with Polygraph
- Effective written and verbal communication skills for technical collaboration
