Artificial Intelligence/Machine Learning Data Engineer
Core
Design, develop, and operationalize AI agents, large-scale data pipelines, and machine learning solutions to support enterprise automation and analytics initiatives.
Role type
AI/ML Data Engineer
Builds
AI agents, data pipelines, and ML solutions for enterprise automation and analytics
Domain
Enterprise AI, Data Engineering, Cloud Infrastructure
Deliverable
production ML models
Required skills
Python, SQL, LLM integration, function-calling patterns, prompt engineering, agent orchestration, MLflow, Azure ML, SageMaker, Kubeflow, TensorFlow, PyTorch, Scikit-Learn, Spark, Databricks, RAG patterns, vector databases, CI/CD pipelines, Docker, Kubernetes, streaming technologies (Kafka, EventHub, Kinesis), cloud platforms (Azure, AWS, GCP)
Preferred skills
Industry certifications (Azure/AWS/GCP Data or AI Engineering), experience with reasoning models and transformer architectures
Technologies
LangChain, Semantic Kernel, LlamaIndex, AutoGen, FAISS, Pinecone, Chroma, Milvus, Redis, Kafka, EventHub, Kinesis
Responsibilities
Design and develop AI agents and toolchains; build scalable data pipelines; deploy ML models securely in regulated environments; integrate AI agents with enterprise APIs and microservices; implement CI/CD and automated testing; optimize embedding and vector database performance
Seniority
Mid-Senior, hands-on IC
