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AI Engineer

NewVision Software & Consultancy Pvt. LtdUnited States🇺🇸United States

Why this role stands out

Leverage your expertise in Generative AI, LLMs, and cloud platforms like AWS or Google Cloud to build innovative AI solutions in this remote, hands-on engineering role. You'll thrive if you have practical experience with AI application development, data pipelines, and deploying production-grade AI solutions, offering a fantastic opportunity to expand your skills in a dynamic tech environment.

Quick overview

SeniorityMid Senior
Work modeRemote
LocationUnited States
AWSC#.NETGPTGoogle CloudJavaLLMPythonGenerative AIAzureJavaScriptTypeScriptPrompt EngineeringCI/CDLangChainLangGraphRAG

Job description

Job Title: Software/AI Engineer

Location: Remote

Job Type: 6 months contract

Job Summary
We are looking for a strong experience in cloud-based data and AI engineering, Generative AI, Large Language Models (LLMs), RAG architectures, and AI application development.
The ideal candidate will have practical experience building and deploying AI/GenAI solutions on AWS or Google Cloud Platform, with Azure experience being a plus. The candidate should be comfortable working with LLMs, RAG architectures, AI frameworks, data pipelines, APIs, and production-grade cloud applications.
This is a hands-on engineering role requiring strong programming skills and the ability to design, develop, integrate, test, troubleshoot, and deploy AI-powered solutions.
Key Responsibilities
  • Design, develop, and deploy cloud-based data and AI solutions using AWS or Google Cloud Platform.
  • Build scalable and production-ready applications using Python and other modern programming languages.
  • Develop and integrate Generative AI and LLM-powered applications.
  • Work with commercial and open-source LLMs such as:
    • OpenAI / GPT
    • Meta Llama
    • Google Gemini
    • Other open-source LLMs
  • Build and implement Retrieval-Augmented Generation (RAG) solutions.
  • Design RAG pipelines including document ingestion, preprocessing, chunking, embeddings, retrieval, reranking, context management, and response generation.
  • Work with LangChain, LlamaIndex, LangGraph, and similar GenAI frameworks.
  • Develop AI agents and graph-based AI workflows where applicable.
  • Build integrations between LLMs, enterprise applications, APIs, databases, data platforms, and cloud services.
  • Develop data ingestion and transformation pipelines supporting AI/ML and GenAI applications.
  • Work with both structured and unstructured data.
  • Implement vector search, embeddings, and vector database solutions.
  • Build APIs and backend services to expose AI capabilities to enterprise applications.
  • Implement monitoring, logging, testing, evaluation, and observability for AI/LLM applications.
  • Optimize AI applications for performance, scalability, reliability, security, and cost.
  • Troubleshoot production issues and continuously improve AI and data engineering solutions.
  • Collaborate with architects, data engineers, software engineers, product teams, and business stakeholders to translate requirements into technical solutions.
Required Skills & Experience
Programming Languages
Strong hands-on programming experience with one or more of the following:
  • Python strongly preferred for AI/GenAI and data engineering
  • C# / .NET
  • Java
  • JavaScript
  • TypeScript
Candidates should be able to write production-quality code and should have strong software engineering fundamentals.
Cloud & Engineering
  • Strong hands-on experience with AWS or Google Cloud Platform.
  • Experience developing and deploying applications/services in a cloud environment.
  • Experience with cloud-native architectures and services.
  • Azure experience is a plus.
  • Experience developing APIs and backend services.
  • Experience with databases and distributed/cloud-based systems.
  • Understanding of containers, serverless technologies, CI/CD, and DevOps practices is preferred.
Generative AI / LLM
Strong practical experience with Generative AI and Large Language Models, including one or more of:
  • OpenAI / GPT models
  • Meta Llama
  • Google Gemini
  • Open-source LLMs
  • LLM APIs and model integration
  • Prompt engineering
  • Embeddings
  • Vector search
  • Model evaluation and optimization
RAG & AI Application Development
Hands-on experience building RAG-based applications, including:
  • Document ingestion
  • Data preprocessing and chunking
  • Embeddings
  • Vector databases / vector search
  • Semantic retrieval
  • Context construction
  • Prompt orchestration
  • Response generation
  • RAG evaluation and optimization
Experience with:
  • LangChain
  • LlamaIndex
  • LangGraph
  • Other equivalent GenAI frameworks

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