GenAI Engineer (GCP)

Scope

• Design, develop, and deploy cutting-edge Generative AI solutions using state-of-the-art LLMs and multimodal models.
• Fine-tune and optimize large language models (LLMs) for domain-specific and enterprise use cases.
• Build and implement GenAI-powered applications leveraging NLP, agentic workflows, and orchestration frameworks such as LangChain and LangGraph.
• Develop scalable, production-ready AI systems on GCP using services such as Vertex AI, BigQuery, and Cloud Run.
• Design and implement Retrieval-Augmented Generation (RAG) pipelines with vector databases such as FAISS or Pinecone.
• Work with distributed computing tools and data pipelines to process large-scale datasets efficiently.
• Collaborate with cross-functional teams to translate business requirements into AI-driven solutions.
• Lead or contribute to R&D initiatives exploring emerging trends in Generative AI and LLMOps.
• Ensure MLOps/LLMOps best practices, including CI/CD, monitoring, versioning, and AI model governance.

Skills

• 4+ years of experience in AI/ML, focused on Generative AI.
• Strong Python skills; experience with Hugging Face Transformers, LangChain, and LangGraph.
• Solid knowledge of LLM fine-tuning, RLHF, and prompt engineering.
• Hands-on experience with Google Cloud Platform, especially Vertex AI, and cloud-native deployments.
• Understanding of MLOps/LLMOps, including CI/CD, pipelines, and monitoring.
• Experience with data pipelines, ETL, vector databases, and RAG architectures.
• Familiarity with Git and collaborative development workflows.
• Strong problem-solving and communication skills, including client-facing experience.