Agentic AI Engineer (Intern)

About the Role

We're looking for a motivated Agentic AI Engineer Intern to join our Z1Agent team. This is a great opportunity to learn how production Agentic AI applications are designed, built, and run.

What is Z1Agent?

Z1Agent is an open-source, autonomous AI-driven K8s incident-resolution and root-cause analysis engine combining L1 cluster triage, L2 telemetry reconstruction/correlation, and L3 deep OS level diagnostics through a pluggable agent/tool architecture. It uses LLM reasoning, agentic workflows, and causal analysis to diagnose failures and generate verified remediation actions.

It also implements a continuous ML lifecycle: production telemetry and incident data are curated into training/evaluation datasets, models are fine-tuned and benchmarked, and validated weights are automatically deployed, creating a closed-loop MLOps pipeline for continuously improving diagnosis and remediation.

Responsibilities

• Develop and maintain backend services and REST APIs using Python3
• Implement CRUD operations and integrate them with relational and NoSQL databases
• Assist in building and integrating AI/ML features (e.g., model inference APIs, LLM-based workflows)
• Write clean, testable, well-documented code
• Containerize applications using Docker
• Help deploy and manage services on Kubernetes clusters
• Debug issues, monitor services, and troubleshoot performance problems
• Collaborate with engineers in code reviews, stand-ups, and sprint planning

Required Skills

• Python 3: Strong fundamentals (data structures, OOP, error handling, virtual environments)
• AI basics: Understanding of core AI/ML concepts, and familiarity with libraries or tools such as scikit-learn, PyTorch, TensorFlow, or LLM APIs
• REST APIs: Knowledge of HTTP methods, status codes, authentication, and API design; experience with FastAPI, Flask, or Django
• CRUD operations: Hands-on experience building Create, Read, Update, Delete functionality end to end
• Databases: Understanding of how databases work, including:
    - SQL (PostgreSQL / MySQL): joins, indexing, normalization, transactions
    - NoSQL (MongoDB / Redis): when and why to use them
    - Basic query optimization and schema design
• Docker: Ability to write Dockerfiles, build images, and run containers
• Kubernetes: Working knowledge of pods, deployments, services, and configuration (ConfigMaps/Secrets)
• Git: Comfortable with version control and pull-request workflows

Good to Have

• Experience with cloud platforms (AWS, GCP, or Azure)
• CI/CD basics (GitHub Actions, GitLab CI, Jenkins)
• Familiarity with Linux and command-line tools
• Knowledge of message queues (Kafka, RabbitMQ)
• Exposure to vector databases and RAG pipelines
• Basic understanding of monitoring tools (Prometheus, Grafana)
• Personal projects, open-source contributions, or a GitHub portfolio

Qualifications

• Currently pursuing or recently completed a Bachelor's/Master's in Computer Science, IT, or a related field
• Strong problem-solving skills and eagerness to learn
• Good communication and teamwork skills

What You'll Gain

• Hands-on experience with production-grade AI and backend systems
• Mentorship from experienced engineers
• Exposure to modern DevOps and cloud-native practices
• Opportunity for a full-time offer based on performance
• Internship certificate and letter of recommendation