We are looking for a Senior Software Engineer specializing in Retrieval-Augmented Generation (RAG) systems, with experience in large language models (LLMs), vector databases, and cloud-based microservices. Your role will focus on building, integrating, and optimizing LLM workflows using LangChain and managing complex infrastructure with AWS services like Lambda and ECS. You'll bring expertise in containerized environments, using Docker, and work with vector databases to power data-driven applications. You will report to a Staff Software Engineer and work remote in the United States or hybrid based on proximity to our office.
You'll Have Opportunity To
RAG Workflow Development: Design and deploy LLM-driven RAG workflows using LangChain and vector databases to provide high-accuracy data retrieval and enhanced content generation.
Vector Database Management: Integrate and manage vector databases like Qdrant for optimized, high-speed vector searches and data retrieval.
Cloud Computing: Use AWS services, including Lambda and ECS, to build serverless architectures and scalable containerized applications.
API & Backend Development: Build APIs with FastAPI and Uvicorn to support low-latency interactions and handle high traffic volumes.
Monitoring & Observability: Implement observability best practices using Datadog, ddtrace, and logging tools to maintain performance and troubleshoot complex workflows.
Qualifications
Required Skills:
Proficiency in LLM and RAG Workflows: experience with LangChain and vector databases, applying RAG techniques for intelligent data retrieval and generation.
Python Proficiency (>=3.11, <3.12): Advanced Python skills, including experience with asynchronous programming.
Proficient in AWS environment
Understanding of MCP Servers
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SMSS Inc. is the best solution company specialized in providing Information Technology and Management Consulting. We provide value for money to our clients by delivering the best quality technical services and solutions at reasonable rates. We also provide the best working environment for our staff and consultants. It is a growing IT services provider having wide array of solutions from Business Strategy Analysis to implementation and execution of Information Technology as well as management aspects of a business entity.
We are looking for a Senior Software Engineer specializing in Retrieval-Augmented Generation (RAG) systems, with experience in large language models (LLMs), vector databases, and cloud-based microservices. Your role will focus on building, integrating, and optimizing LLM workflows using LangChain and managing complex infrastructure with AWS services like Lambda and ECS. You'll bring expertise in containerized environments, using Docker, and work with vector databases to power data-driven applications. You will report to a Staff Software Engineer and work remote in the United States or hybrid based on proximity to our office.
You'll Have Opportunity To
RAG Workflow Development: Design and deploy LLM-driven RAG workflows using LangChain and vector databases to provide high-accuracy data retrieval and enhanced content generation.
Vector Database Management: Integrate and manage vector databases like Qdrant for optimized, high-speed vector searches and data retrieval.
Cloud Computing: Use AWS services, including Lambda and ECS, to build serverless architectures and scalable containerized applications.
API & Backend Development: Build APIs with FastAPI and Uvicorn to support low-latency interactions and handle high traffic volumes.
Monitoring & Observability: Implement observability best practices using Datadog, ddtrace, and logging tools to maintain performance and troubleshoot complex workflows.
Qualifications
Required Skills:
Proficiency in LLM and RAG Workflows: experience with LangChain and vector databases, applying RAG techniques for intelligent data retrieval and generation.
Python Proficiency (>=3.11, <3.12): Advanced Python skills, including experience with asynchronous programming.
Proficient in AWS environment
Understanding of MCP Servers
Required profile
Experience
Spoken language(s):
English
Check out the description to know which languages are mandatory.