Job Description
Hybrid Details:
Onsite Tuesday-Thursday Duration:
6 months to start Job Description:
We are seeking a highly skilled AI Engineer with strong expertise in customized Large Language Models (LLMs) and hands-on experience with the Databricks platform. The ideal candidate will design, build, fine-tune, and deploy enterprise-grade generative AI solutions , modern AI frameworks, and cloud technologies. Key Responsibilities:
Design, develop, and deploy customized LLM-based applications Build scalable Generative AI and RAG (Retrieval-Augmented Generation) solutions on Databricks Lakehouse architecture. Fine-tune and optimize open-source and proprietary LLMs using enterprise datasets. Develop prompt engineering frameworks and AI orchestration workflows. Work with Databricks Mosaic AI, MLflow, Vector Search, and Unity Catalog. Build and manage vector databases, embeddings pipelines, and semantic search solutions. Integrate AI solutions with enterprise applications, APIs, and cloud platforms. Optimize model performance, scalability, inference latency, and cost efficiency. Implement AI governance, monitoring, security, and responsible AI practices. Collaborate with business stakeholders, data engineers, and product teams to deliver AI solutions. Support AI model deployment, MLOps pipelines, and production monitoring. Required Skills & Qualifications:
Strong hands-on experience with Databricks and Lakehouse architecture. Experience with Databricks Mosaic AI, MLflow, Delta Lake, and Unity Catalog. Strong programming skills in Python and SQL. Hands-on experience with LLMs such as GPT, Llama, Mistral, Claude, or similar models. Experience with RAG architectures, embeddings, and vector search implementations. Knowledge of LangChain, LangGraph, Semantic Kernel, or similar AI orchestration frameworks. Experience with cloud platforms such as AWS, Azure, or Google Cloud Platform. Familiarity with APIs, Docker, Kubernetes, and microservices architecture. Understanding of AI governance, model evaluation, and monitoring. Preferred Qualifications:
Experience deploying GenAI applications in enterprise environments. Knowledge of distributed computing and Spark optimization. Experience with Databricks Model Serving and AI Gateway. Familiarity with CI/CD and MLOps practices. Experience with multimodal AI models and AI agents. Technologies & Tools Databricks, Mosaic AI, MLflow, Delta Lake Python, SQL, PyTorch, TensorFlow OpenAI API, Hugging Face LangChain, LangGraph Vector databases: Pinecone, FAISS, ChromaDB AWS, Azure, Google Cloud Platform Docker, Kubernetes, GitHub Actions Talent Groups is an equal opportunity employer that values diversity and inclusion. All qualified applicants will receive consideration without regard to protected characteristics. The listed compensation range represents a good-faith estimate and may vary based on experience, skills, education, certifications, market conditions, client budget, and location, in accordance with applicable pay transparency laws.
