AI/ML Engineer (LangChain + RAG + Multi-Agent)
Skills
About the role
We are looking for an experienced AI/ML Engineer with strong expertise in LangChain, RAG architectures, vector databases, and multi-agent systems. The role involves building intelligent pipelines, optimizing LLM workflows, and developing predictive models using Python.
Design and implement multi-agent architectures using LangChain
Build autonomous agent systems with secure data and SQL access
Develop agent orchestration workflows for complex operations
Implement Retrieval-Augmented Generation (RAG) pipelines
Design embedding strategies and vector database structures for efficient retrieval
Optimize retrieval quality, context windows, and model responses
Build predictive models related to performance analytics and scoring
Create models & Develop algorithms for business
Craft and optimize prompts for LLM-based features and automations
Implement few-shot, chain-of-thought, and structured prompting techniques
Evaluate, test, and iterate on prompt performance across different use cases
Requirements
Bachelors or Masters degree in Computer Science, AI/ML, Data Science, or related field
3+ years of experience in AI/ML engineering with hands-on LLM development
Strong proficiency in Python
Experience with TensorFlow, PyTorch, or scikit-learn
Practical experience with LangChain, LlamaIndex, or similar LLM frameworks
Experience designing and deploying RAG systems
Hands-on experience with vector databases such as Pinecone, Weaviate, or Opensearch
Strong understanding of transformer architectures and modern LLM capabilities
Preferred Qualifications
Experience working with cloud-based AI/ML services
Experience developing multi-agent or agentic workflows
Familiarity with model deployment, monitoring, and MLOps practices
Work Location: Remote
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