What are the responsibilities and job description for the Senior AI/ML Engineer – LLM and Agentic AI Systems - Fulltime position at Vega Intellisoft Inc.?
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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Salary : $130,000 - $145,000