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-Build LLM-powered applications, AI agents, and intelligent automation solutions.
-Develop multi-agent orchestration, planning, tool usage, memory constructs, and task decomposition workflows.
-Utilize frameworks such as LangChain, CrewAI, AutoGen, Semantic Kernel.
-Integrate with OpenAI, Azure OpenAI, Anthropic, and other LLM APIs.
-Implement Retrieval-Augmented Generation (RAG) architectures with vector databases (Pinecone, FAISS, Chroma, Weaviate).
-Develop and maintain ML workflows, embeddings, finetuning, and model validation pipelines.
-Design REST/gRPC APIs, microservices, and enterprise integration layers.
-Deploy AI solutions on cloud platforms (Azure preferred; exposure to AWS/GCP) with CI/CD using Azure DevOps, GitHub Actions, or Jenkins.
-Apply secure coding, model governance, and responsible AI principles.--
Job ID: 144926671
Skills:
Gen AI, AI and Machine Learning algorithms, RAG neural networks
Skills:
snowflake , MLops, Docker, Terraform, Data Integration, Azure, AWS, generative AI, data orchestration
Skills:
Java, Node.js, Gcp, Azure, Python, AWS, LangChain, LLMs, Hugging Face Transformers, vector databases, MLflow, embedding models, Vertex AI, Kubeflow, Transformers, RAG, Diffusion models
Skills:
data engineering , S3, Kafka, Emr, Data Modeling, Redshift, Sql, Apache Airflow, Kinesis, Spark, Python, AWS Cloud services, DataOps practices, AWS Step Functions, CI CD, SageMaker, pipeline orchestration, Lake Formation, Glue
Skills:
containerization , Python, Apis, Machine Learning, MLops, LangChain, LLMs, RAG architectures, LLMOps, Generative AI, LangGraph, vector databases
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