AI engineer
- Posted 19 hours ago
- Be among the first 40 applicants
Job Description
What the requirement prioritizes
- Engineering first: Python / FastAPI, APIs, containerization, EKS / Kubernetes, architecture and production debugging.
- Hands-on agentic work: ideally 2-3 years; 1+ year is acceptable with strong fundamentals and genuine production experience.
- At least one agentic framework or equivalent. Custom components count only with a clear rationale and engineering trade-offs.
- Personal deployment ownership, evaluation, observability and monitoring. A demo or conceptual explanation alone is not enough.
- Independent delivery in a lean two-person AI engineering pod. Quality over CV volume.
More Info
Key Skills
agentic framework
EKS
production debugging
observability
About Company
Skills:
C, Ibm Cloud, Linux System Administration, Tensorflow, Jenkins, Git, Pytorch, Gcp, Terraform, Ansible, Openshift, Shell scripting, Azure, Kubernetes, AWS, Generative AI, vLLM, GitHub Actions
Skills:
Git, Terraform, Networking Basics, Azure DevOps, Private endpoint concepts, Environment variables, Key Vault, Prompt transcript logging, Log Analytics, AI Gateway, Artifact handling, CI/CD pipelines, Resource Deployment, Deployment validation, RAG observability, Infrastructure-as-Code, Azure Monitor, Application Insights, Monitoring and diagnostic configuration, Azure core services
Skills:
Ml, Nlp, MLops, Python, LangChain, vector search, GenAI, embeddings, LLMs, conversational AI, Hugging Face, vector databases, LangGraph, RAG
Skills:
Machine Learning, Apis, Predictive Analytics, Python, LangChain, MCP A2A-based architectures, LangSmith, Performance Reporting, Feature engineering, LangGraph, AutoGen, model validation, Automated retraining, Monitoring