DGLiger Consulting
Sr. Gen AI Engineer
- Compensation
- Not disclosed
- Location
- Remote
- Work setup
- Remote
- Seniority
- Senior
- Employment
- Not specified
- Experience
- Not specified
- Category
- Ai engineering
- Posted
Skills
Must have
- Hands-on experience building and deploying enterprise-grade GenAI applications.
- Strong software engineering fundamentals and production-level Python development.
- Experience integrating LLMs with enterprise data using Databricks.
- Ability to translate business requirements into scalable AI solutions.
- Exposure to marketing or customer service AI use cases will be preferred.
Full description
We are looking for experienced GenAI Engineers who can design, develop, and deploy production-grade AI applications, with strong expertise in LLMs, agentic AI, RAG, and Databricks.
Requirements:
- Hands-on experience building and deploying enterprise-grade GenAI applications.
- Strong software engineering fundamentals and production-level Python development.
- Experience integrating LLMs with enterprise data using Databricks.
- Ability to translate business requirements into scalable AI solutions.
- Exposure to marketing or customer service AI use cases will be preferred.
Key Skills and Experience:
- Generative AI and LLMs: RAG, LangGraph, Agentic AI, Prompt Engineering, Tool/Function Calling, LLM Evaluation, and Guardrails.
- Databricks AI: Mosaic AI, Vector Search, Model Serving, Agent Framework, MLflow, and LLM Tracing.
- Data Engineering: PySpark, Spark SQL, Delta Lake, Medallion Architecture, Unity Catalog, and Databricks Workflows.
- Cloud and Development: Python, Azure OpenAI/AWS Bedrock, FastAPI, Docker, CI/CD, and Git.
- AI Optimization and Security: Hallucination Reduction, LLM Monitoring, Token/Latency Optimization, Data Privacy, and AI Governance.
- Additional Advantage: MCP, Hugging Face, vLLM, fine-tuning, Kubernetes, Terraform, and streaming.