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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:
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
- 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
- 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