Senior AI/ML Engineer – Agentic AI
2 weeks ago
About the Role We are looking for ahighly skilled and innovative AI/ML Engineer (Contract role)to join ourAgentic AI and Generative AI (GenAI)development team. The ideal candidate will be hands-on in building and optimizingMultimodal RAG architectures, intelligent agents, and enterprise-grade GenAI automation systems . This role offers a unique opportunity to work on next-generationAgentic AI frameworks , combiningLLMs, multimodal retrieval, and automation pipelinesfor global enterprise use cases.Key Responsibilities Design, build, and deployMultimodal RAG architecturesandLangGraph-based Agentic AI systemsfor enterprise automation. Develop and optimizechunking strategies, embedding pipelines , andvector database integrations(Vertex AI, PGVector, Pinecone). IntegrateLLMs (Gemini 2.5, Gemma, LLaMA 4, etc.)into GenAI workflows and automation pipelines. Implement and maintainCI/CD pipelines , supportingMLOps/LLMOpsframeworks for continuous delivery. Collaborate with cross-functional teams to ensurescalable deploymentonGCP (Vertex AI)platforms. Continuously evaluate, monitor, and fine-tune models forprecision, recall, relevance, faithfulness , andcost efficiency . Contribute to the development ofevaluation frameworks (e.g., RAGAS)andAI efficacy dashboards.Required Skills & Experience Minimum4+ years of experienceinAI/ML model developmentwith a focus onGenAI, RAG, or Agentic AIsystems. Proven hands-on experience with: Vector databases:PGVector, Pinecone, or similar Multimodal data processing:text, image, audio embeddings and chunking Embedding modelsandvector search optimization Practical knowledge ofLangChain, LangGraph , andLLMOpstoolkits. Familiarity withGCP Vertex AIor equivalent ML platforms. Experience withCI/CD ,MLflow , or other MLOps automation pipelines. Exposure toprompt engineering, fine-tuning , andLLM model integration .Good to Have Bachelor’s or Master’s degree inComputer Science, AI/ML, Data Science , or related disciplines. GCP/AWS/ML certificationsare an advantage. Contributions toopen-source AI projectsor publications inGenAI / RAG / Agentic AIdomains. Strong problem-solving ability and a mindset forrapid prototyping and experimentation .
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