Overview
Dice is the leading career destination for tech experts at every stage of their careers. Our client, Vega Intellisoft Inc., is seeking the following. Apply via Dice today!
Senior AI/ML Engineer – LLM & Agentic AI Systems – Hybrid
Job Description:
We are looking for a Senior AI/ML Engineer with strong expertise in Large Language Models (LLMs), Agentic AI frameworks, MLOps, and cloud-based AI platforms. The ideal candidate should have hands-on experience building production-grade AI systems, developing scalable ML pipelines, and supporting enterprise AI initiatives in cloud environments.
Key Responsibilities:
Design and support enterprise AI/ML solutions using modern LLM and agentic AI frameworks Build orchestration workflows integrating AI models, enterprise services, and external AI tools Develop and optimize RAG-based AI solutions and prompt engineering strategies Support LLM fine-tuning, model evaluation, and continuous model improvement initiatives Build monitoring, model versioning, retraining, and governance workflows for production AI systems Collaborate with data engineering and cloud teams on scalable AI platform implementations Develop tooling for AI experimentation, model lifecycle management, and operational automation Participate in architecture discussions and technical design reviews for AI/ML platforms Maintain technical documentation, model workflows, and deployment standards Support secure and scalable AI deployments aligned with enterprise governance practices
Required Skills:
5+ years of experience in AI/ML engineering or machine learning systems development Strong hands-on experience with LLM fine-tuning and production AI systems Experience with LangChain, LangGraph, Agentic AI frameworks, or similar orchestration platforms Strong Python development experience for AI/ML pipelines and platform tooling Experience with TensorFlow, PyTorch, Hugging Face, MLflow, or related ML frameworks Strong experience with RAG architectures, prompt engineering, and AI model evaluation Experience with MLOps practices including model deployment, monitoring, versioning, and retraining Hands-on experience with Google Cloud Platform services such as Vertex AI, BigQuery, GCS, Dataflow, or Cloud Composer Experience working with structured and unstructured datasets in enterprise AI environments Strong understanding of cloud-based AI platform architecture and governance practices Strong communication and technical documentation skills
Preferred Skills:
Experience with multi-agent AI systems and tool orchestration patterns Experience with telemetry or event-streaming data environments Google Cloud ML certifications preferred Experience working in regulated or enterprise-scale environments preferred
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Level of experience (years):
Senior (5+ years of experience)
