Key skills
AI/ML applicationsCloud infrastructureContainerization DockerContainerization KubernetesRelational databasesGitCollaborative developmentRAG pipelinesLLM evaluation techniquesPythonAIMLLLMRAGFastAPIDjangoKubernetesDockerCI/CD
About this role
VectorShift is building AI enterprise workflow automation, converting complex manual processes into automated AI systems. As an AI Engineer, you will work on core AI infrastructure and ship AI-powered features that are performant, reliable, and secure, contributing across the full stack.
Responsibilities:
- Design, build, and deploy AI-powered features in production, including RAG systems, multi-agent orchestration, and evaluation frameworks
- Own backend services and APIs end-to-end (Python / FastAPI / Django)
- Build data pipelines for model training, evaluation, and continuous improvement
- Collaborate with founders, product, and design to ship high-impact features
- Ensure scalability, performance, and security across the platform
- Contribute to engineering best practices, code quality, and technical decision-making
Requirements:
- 2+ years of professional software engineering experience
- Hands-on experience building and deploying AI/ML applications in production environments
- Solid understanding of relational databases and data modeling
- Experience with cloud infrastructure, containerization (Docker, Kubernetes), and CI/CD pipelines
- Familiarity with RAG pipelines, LLM orchestration, or AI agent architectures
- Experience with Git and collaborative development workflows
- Familiarity with LLM evaluation techniques and tools for measuring reliability
- Strong problem-solving instincts and a bias toward shipping
- Experience working in or building for large enterprises
- Prior startup experience or comfort operating in high-ambiguity environments