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Artificial Intelligence Engineer
Skills
Computer ScienceDevopsAnalytical SkillsApache SparkAzure Devops ServicesData ScienceFundamentals
What the job involves
The main requirements, responsibilities and hiring steps.
Requirements
- Proven applied Agentic AI engineering experience with production or client project evidence
- Strong experience designing and implementing modern multi-agent architectures
- Hands-on expertise with agentic AI frameworks and orchestration tools such as LangGraph CrewAI AutoGen Microsoft Semantic Kernel or LangChain
- Experience contributing to AI solution architecture and system design
- Strong programming skills in Python with R as a plus
- Experience with machine learning frameworks such as TensorFlow PyTorch or Scikit-learn
- Experience developing and deploying AI ML models into production
- Knowledge of LLMs NLP RAG prompt engineering and AI workflow automation
- Experience with cloud platforms such as AWS Azure or Google Cloud Platform
- Familiarity with Spark Hadoop or other big data technologies
- Experience working in Agile Scrum environments using Azure DevOps or similar tools
- Excellent analytical communication and problem-solving skills
Nice to have
- Innovative
- Analytical
- Collaborative
- Problem-solving
- Agile-minded
Day to day
- Design and deploy agentic AI workflows for real-world business use cases
- Build and orchestrate multi-agent systems using modern frameworks and tools
- Contribute to AI solution architecture system design and production deployment
Hiring process
- Submit updated resume
- Share brief summary of Agentic AI projects
- Include frameworks and tools used
- Describe specific contributions