Senior AI/ML Engineer – Agentic AI
6 days ago
About the RoleWe are looking for a highly skilled and innovative AI/ML Engineer (Contract role) to join our Agentic AI and Generative AI (GenAI) development team. The ideal candidate will be hands-on in building and optimizing Multimodal RAG architectures, intelligent agents, and enterprise-grade GenAI automation systems.This role offers a unique opportunity to work on next-generation Agentic AI frameworks, combining LLMs, multimodal retrieval, and automation pipelines for global enterprise use cases.Key ResponsibilitiesDesign, build, and deploy Multimodal RAG architectures and LangGraph-based Agentic AI systems for enterprise automation.Develop and optimize chunking strategies, embedding pipelines, and vector database integrations (Vertex AI, PGVector, Pinecone).Integrate LLMs (Gemini 2.5, Gemma, LLaMA 4, etc.) into GenAI workflows and automation pipelines.Implement and maintain CI/CD pipelines, supporting MLOps/LLMOps frameworks for continuous delivery.Collaborate with cross-functional teams to ensure scalable deployment on GCP (Vertex AI) platforms.Continuously evaluate, monitor, and fine-tune models for precision, recall, relevance, faithfulness, and cost efficiency.Contribute to the development of evaluation frameworks (e.g., RAGAS) and AI efficacy dashboards.Required Skills & ExperienceMinimum 4+ years of experience in AI/ML model development with a focus on GenAI, RAG, or Agentic AI systems.Proven hands-on experience with:Vector databases: PGVector, Pinecone, or similarMultimodal data processing: text, image, audio embeddings and chunkingEmbedding models and vector search optimizationPractical knowledge of LangChain, LangGraph, and LLMOps toolkits.Familiarity with GCP Vertex AI or equivalent ML platforms.Experience with CI/CD, MLflow, or other MLOps automation pipelines.Exposure to prompt engineering, fine-tuning, and LLM model integration.Good to HaveBachelor’s or Master’s degree in Computer Science, AI/ML, Data Science, or related disciplines.GCP/AWS/ML certifications are an advantage.Contributions to open-source AI projects or publications in GenAI / RAG / Agentic AI domains.Strong problem-solving ability and a mindset for rapid prototyping and experimentation.
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